The ‘online high street’ or the high street online? The implications for the urban retail hierarchy

The U.K. has the greatest proportion of online sales in Europe. This study seeks to explore the differential effects of online retailing on the (evolving) hierarchy of shopping centres by examining current trends and underlying forces. The overall objectives of the paper are to qualify and explore the influence of online retailing in the decision-making processes of leading retailers today; and to assess how virtual influences become manifest in the tangible built environment and have impacted the retail hierarchy? It differentiates online retail trends by sector and retailer size, and examines the consequences for different types of shopping centres. The empirical research is based on the changing location of stores of a major fashion retailer and interviews with three of Britain’s leading retailers that have seen the more substantial increase in online turnover in recent years. Major retailers are found to have integrated online offerings, such as click and collect, into a ‘multi-channel’ retailing approach. Online retailing has therefore become an inherent and central element within large retailers’ business and therefore real estate strategies, with considerations such as online marketplace penetration and possible ‘cannibalisation’ coming to the fore in decision-making about store location. Online retail sales are, to a degree, drawing sales away from shopping centres but its impact on the existing shopping hierarchy is largely to reinforce established long-term trends driven by the motor age and the shift to out of town retailing. This is symbolised by the largest ‘high street’ fashion retailer now having more branches in retail parks than town centres. Out of town shopping centres for example are benefitting because of the ease of goods collection offered by these locations.     

Basket Composition and Choice Among Direct Channels: A Latent State Model of Shopping Costs

Shoppers of multi-channel retailers often place orders using different channels on different shopping occasions. The differential use of channels is related to both basket composition and channel characteristics, such as the ability of the channel to provide additional information that resolves uncertainty about the purchase. In this paper, we examine the impact of basket composition on the choice among direct channels. We develop a two-stage, shopping cost model with two, latent states. Given a shopping basket, the shopper first decides if she needs additional information about items in the basket. If she is uncertain about the items in the basket meeting her needs, she uses an information rich channel, such as the retailer's website or call center, and risk reduction costs become salient in addition to the other shopping costs. If she does not require additional information, she places her order by choosing among all available channels, and she may incur a welfare loss from making a purchase that does not optimally meet her needs. We operationalize welfare loss with Shannon information and various metrics based on purchase history.Our empirical setting is a data set from a catalog retailer that offers multiple direct channels. Our estimates show that basket composition impacts channel choice. Large baskets shift to the Internet channel, suggesting that the Internet channel has lower ordering costs. High-risk baskets shift to call centers and this suggests that the call center has lower risk reduction costs. Collectively these estimates provide evidence for the notion of channel specialization—some channels are better at addressing certain shopping costs compared to others. Our estimates also show that electronic self-service channels have high initial access costs and a significant learning curve compared to the call center suggesting that these channels might be better suited to heavy users. We use the estimated model to quantify the value of channels, to identify categories that need risk reduction, and to segment and target shoppers for Internet ordering based on basket size and the potential to accumulate experience.     

Retail Market Power in a Shopping Basket Model of Supermarket Competition

Supermarket retailers typically operate with relatively low margins, suggesting a highly competitive retail environment. However, despite the fact that consumers purchase an entire shopping basket at a time from supermarkets, this evidence is largely based on models of retail competition with single-category purchases. In this paper, we develop and test an empirical model of retail price competition that explicitly accounts for the effect of demand complementarity among items in consumer shopping baskets. Relative to the case where consumers purchase products with independent demands, we demonstrate that equilibrium prices are higher for all items when retailers take demand-complementarity into account. Our findings indicate that non-price strategies intended to encourage complementarity, such as co-merchandising, strategic shelf-positioning, or featuring complementary goods tend to soften price competition, and lead to higher equilibrium prices.     

A Comparison of Return Rate Calculation Methods: Evidence from 16 Retailers

The product return rate (RR) is an important metric for retailers; even small RR changes can significantly impact retailers’ profit. Companies and researchers typically favor and employ one of three methods to calculate the RR: based on the number of returned items, these items’ revenue, or their profit contribution. Interviews with 24 managers and industry experts reveal that two methods, item-based and revenue-based, are often used. However, little is known about how much the interpretation of RRs depends on the calculation method. In this article, the authors rely on extensive datasets to investigate these potential differences empirically. Analyzing more than 8 million transactions at sixteen different retailers, the authors find that RRs calculated via the three methods differ on average by 24.3%. The size of these differences makes cross-sectional comparisons of RRs calculated via different methods difficult. In contrast, the authors find that the developments of the RRs over time are similar, which allows for a meaningful time-series comparison of RR developments, regardless of the method. Finally, this research shows that all three calculation methods result in RRs that are equally insightful (leading) indicators of relevant retailer performance metrics.     

Measuring Cross-Category Specials Purchasing: Theory, Empirical Results, and Implications

The typical Hi-Lo grocery retailer offers consumers thousands of price specials each week to build traffic and influence economic performance. Retailer reliance on price specials may engender heavy cross-category specials purchasing by shoppers. Retailers contend that high cross-category specials purchasing can damage profitability because many of the specials presented to consumers have reduced gross margins. The present study measures the level of cross-category specials purchasing in a Hi-Lo grocery market and develops and tests a model of the determinants of cross-category specials purchasing using shopping basket level data, information from surveys of shoppers, and retailer promotions. The results of the study show about 39% of all items purchased on a shopping trip were on special and that about 30% of consumers surveyed were highly sensitive to price specials, purchasing more specials than regular priced items on their shopping trip. The findings indicate that the consumer search behaviors, such as reading flyers, significantly affected the level of cross-category specials purchasing as did the demographic variable - household income. The study concludes with a series of practical implications for managers to help them gain profitable shopping baskets and set of implications for researchers interested in developing new insights on cross-category specials purchasing.     

The Role of Retail Competition,Demographics and Account Retail Strategy as Drivers of Promotional Sensitivity

We study the determinants of sensitivity to the promotional activities of temporary price reductions, displays, and feature advertisements. Both the theoretical and empirical literatures on price promotions suggest that retailer competition and the demographic composition of the shopping population should be linked to response to temporary price cuts. However, datasets that span different market areas have not been used to study the role of retail competition in determining price sensitivity. Moreover, little is known about the determinants of display and feature response. Very little attention has been focused on retailer strategic decisions such as price format (EDLP vs. Hi-Lo) or size of stores. We assemble a unique dataset with all U.S. markets and all major retail grocery chains represented in order to investigate the role of retail competition, account retail strategy, and demographics in determining promotional response. Previous work has not simultaneously modeled response to price, display, and feature promotions, which we do in a Bayesian Hierarchical model. We also allow for retailers in the same market to have correlated sales response equations through a variance component specification. Our results indicate that retail strategic variables such as price format are the most important determinants of promotional response, followed by demographic variables. Surprisingly, we find that variables measuring the extent of retail competition are not important in explaining promotional response.     

An Upbeat Crowd: Fast In-store Music Alleviates Negative Effects of High Social Density on Customers’ Spending

Research suggests that in-store crowding can lower customers’ spending, thus limiting overall benefits of high store frequentation. Here, we propose that this negative effect can be mitigated by adjusting store ambiance, specifically by using certain types of in-store music. To test this idea, we conducted a longitudinal field experiment in which we manipulated in-store music tempo and measured social density in six European retail stores. Analyzing over 40,000 individual shopping baskets, we found that social density had an inverted u-shape effect on customer spending. This effect was moderated by in-store music tempo, such that fast music strongly increased spending under high-density conditions. The increase in shopping basket value was driven by customers buying more items rather than buying items that were more expensive. Fast music thus alleviated negative effects of social density. We discuss the theoretical implications of these findings and describe how practitioners can use in-store music to counter negative effects of high customer density.     

Optimal retail sales strategies for old and new products in monopoly and horizontal competition scenarios

Advances in technology have made product updates more frequent and allowed consumers to choose different versions of the same product based on their preferences. It is crucial for retailers to understand how to formulate optimal sales strategies based on those different consumer preferences. To this end, we develop game models that consider the heterogeneity of consumer preferences under both monopoly and horizontal competition scenarios and perform the sensitivity analysis to examine the impact of consumer proportions and consumer preferences on retailers’ sales strategies. The results show that (i) regardless of competition or monopoly status, the original retailer can always maximize profit by setting prices based on the market share of traditional consumers, as long as the retailer sells both new and old versions of the product; (ii) the greater the competitive advantage of the competitor, the more advantageous the hybrid sales mode; (iii) if the price of the old product is below a certain threshold, there will be a positive profit for the original retailer when selling both the old and new products; and (iv) when consumer acceptance of competing retailers is lower, entering the retail market is not a good choice for competing retailers.     

Online and offline retailing: What we know and directions for future research

The fast-paced growth of e-commerce is rapidly changing consumers’ shopping habits and shaping the future of the retail industry. While online retailing has allowed companies to overcome geographic barriers to selling and helped them achieve operational efficiencies, offline retailers have struggled to compete with online retailers, and many retailers have chosen to operate both online and offline. This paper presents a review of the literature on the interaction between e-commerce and offline retailing, highlighting empirical findings and generalizable insights, and discussing their managerial implications. Our review includes studies published in more than 50 different academic journals spanning various disciplines from the inception of the internet to present. We organize our paper around three main research questions. First, what is the relationship between online and offline retail channels including competition and complementarity between online and offline sellers as well as online and offline channels of an omnichannel retailer? Under this question we also try to understand the impact of e-commerce on market structure and what factors impact the intensity of competition /complementarity. Second, what is the impact of e-commerce on consumer behavior? We specifically investigate how e-commerce has impacted consumer search, its implications for price dispersion, and user generated content. Third, how has e-commerce impacted retailers’ key managerial decisions? The key research questions under this heading include: (i) What is the impact of big data on retailing? (ii) What is the impact of digitization on retailer outcomes? (iii) What is the impact of e-commerce on sales concentration? (iv) What is the impact of e-commerce and platforms on pricing? And (v) How should retailers manage product returns across online and offline channels? Under each section, we also develop detailed recommendations for future research which we hope will inspire continued interest in this domain.     

Evaluating the impact of VAT-free promotion: the role of loyalty program membership and category characteristics

This study examines the impact of value-added tax (VAT)–free promotions on sales performance. VAT-free promotions are a recently adopted form of price promotions where consumers are exempted from paying the VAT amount across almost all products in the assortment during a limited number of days. They are typically organized once per year and surrounded by a large amount of media attention from the involved retailer. To test the effects of this promotion on store and category sales, and investigate the differences between loyalty program (LP) members and non-LP members, the authors use scanner data from a Dutch durable goods retailer across a range of categories. The results show that VAT-free promotions positively impact store performance. Moreover, the findings indicate that more non-LP members are attracted to the store and that they increase the amount they spend in the store. While LP members also spend more in the store, this increase in shopping basket size does not compensate for the significant drop in the number of LP members that visit the store, leading to an overall decrease in sales coming from LP members during VAT-free days. We furthermore find that the positive effect of VAT-free promotions for non-LP members (rather than LP members) generalizes across all investigated categories. Our results provide key insights for retailers and direct marketers with regard to the effectiveness of VAT-free promotions in order to strategically segment the customer base.

     

Why is Price Dispersion Higher Online than Offline? The Impact of Retailer Type and Shopping Risk on Price Dispersion

When physically similar products, of similar quality, are offered by retailers both online and offline, we often observe that the dispersion in prices of these products online is greater than the price dispersion offline. This observation runs counter to early theories that suggested price dispersion online would be smaller than that offline due to the ease of search and information availability online. This paper investigates and provides an explanation for this puzzling phenomenon by examining the impact of two important drivers of price dispersion: retailer type and consumers’ shopping risk. Retailer type refers to whether a retailer is a pure offline, pure online, or dual channel retailer. Shopping risk is defined as the product of consumers’ perceived risk of shopping and the transaction uncertainty related to shopping at different types of retailers.A game-theoretic approach is adopted to model consumers’ price search and product purchase, as well as price competition within and across retailer types in online and offline markets. Equilibrium pricing strategies are derived for different retailer types competing for different consumer segments with different levels of perceived shopping risk. The impact of retailer type and shopping risk on online versus offline price dispersion are quantified, and conditions when price dispersion is greater online than offline are identified.Results indicate that price dispersion is greater online when the number of pure online retailers is sufficiently large and is increasing in the number of pure online retailers. In addition, a reduction in online shopping risk may actually increase online price dispersion. Results further suggest that even without any online sales, dual channel retailers should maintain their online presence for the purpose of information dissemination, which justifies the importance for pure offline retailer to incorporate webrooming strategies, where consumers can search for prices online but purchase offline.     

The dark side of multiunit discounts: Multiunit discounts reduce rest of basket revenue

Multiunit discounts refer to the practice of offering a discount on purchase of multiple units of a product. An example of multiunit discounts, which are commonly used by retailers, is ‘3 for $10’. While past research suggests that multiunit discounts generate higher sales than per-unit discounts, there is no research on how such discounts affect sales of other products in the store. We argue that consumers exposed to multiunit discounts may purchase the products offered as such to benefit from the deal. These customers, however, will spend less on other products, resulting in lower revenue from the rest of the basket during the shopping trip. Based on theoretical insights, we propose why such an effect could occur and test our arguments using store data and a lab experiment. The findings of this research suggest that multiunit discounts have a multifaceted impact on consumer decision-making. We also discuss the theoretical, managerial, and methodological contributions of this research.     

Chief stores officer and retailer performance

This research investigates the performance implications for retailers of having a chief stores officer (CSO) in the top management team (TMT). Using a matched sample consisting of 120 public retailers, we find that CSO presence is positively associated with 3 different performance metrics, namely, comparable store sales, profit per store, and Tobin's q. We also identify a partial mediating mechanism and find that CSO presence improves retailer performance through enhanced inventory turnover. Our results are robust to controlling for a series of TMT characteristics (such as chief marketing officer presence, chief operating officer presence, and TMT diversity), time-invariant unobservables at the retailer level, different measures of key variables, and alternate model specifications. As the first study that explores the phenomenon of CSO presence, our findings have important implications for public retailers on how to leverage marketing expertise in the TMT to improve performance.     

Consumer response to retailer use of cause-related marketing: Is more fit better?

Although marketers increasingly rely upon cause-related marketing strategies to increase sales, controversy exists regarding whether a retailer should partner with causes offering high or low fit levels with its core business practices. The present investigation extends prior research by examining how retailer–cause fit affects consumer evaluations of retailers’ cause-related marketing strategies. The results indicate that the effects of retailer–cause fit are moderated by consumer perceptions of the retailer's motive for engaging in cause-related marketing (Study 1), by the affinity that consumers hold for the social cause component of the campaign (Study 2), as well as by the interactive effects associated with the two moderators (Study 3).     

Modifying Conjoint Methods to Model Managers' Reactions to Business Environmental Trends: An Application to Modeling Retailer Reactions to Sales Trends

This article proposes and demonstrates how conjoint methods can be adapted to allow the modeling of managerial reactions to various changes in economic and competitive environments and their effects on observed sales levels. Because in general micro-level data on strategic decision making over time are difficult and expensive to obtain, this approach can be of much value to the further study of managerial strategic behavior and market dynamics. In our application we model retailer reactions to changes in their sales, focusing in particular on the actions that affect the demand for retail space and possibilities to improve retail sites. Choice responses to hypothetical sales and environmental trend scenarios are collected from 183 retailers and used to estimate to logit regression model that predicts retailers' probabilities of choosing actions. The model results confirm that retailers are more likely to take action when sales go down than when they go up, and also that they react more quickly if sales go down. It is also found that retailers are more reluctant to change the positioning of their store when confronted with a sales increase than when confronted with a sales decrease. The model is compared with a non-experimental model that is based on retailers' reactions to the trends they report to have observed for their own stores. The article concludes with a discussion of the implications of this research for the further development of conjoint-like approaches to studying entrepreneurial behavior.     

Driving In-Role and Extra-Role Brand Performance among Retail Frontline Salespeople: Antecedents and the Moderating Role of Customer Orientation

The organizational frontline in retail represents the frontline for an entire supply chain. This channel structure distances the branded supplier from the end consumer and makes the supplier dependent on a retail frontline salesperson that (1) it does not control and (2) also represents competing brands. This study reveals mechanisms that the supplier may use to influence retail frontline salespeople. We demonstrate the importance of consumer marketing programs and supplier representatives in building brand identification between the manufacturer’s brand and the retail frontline employee that translates into increased brand sales, while also revealing the role of rewards programs in stimulating brand-specific extra-role behaviors. Interestingly, retail frontline customer orientation, built by the retailer, diminishes the effect of brand extra-role behaviors toward the focal brand on the focal brand’s sales, providing an informal control mechanism for retailers to protect its objectives. The results of this study have powerful ramifications for both retailers and suppliers in achieving both their mutual, and sometimes differing, objectives related to the retail frontline.     

考虑零售商销售努力的双渠道供应链定价策略研究

随着电子商务市场的日益成熟,制造商建设线上直销渠道来适应新的商品销售环境成为趋势。制造商线上直销渠道的建立占领了部分原本属于线下零售渠道的市场份额,对线下零售渠道造成冲击。针对双渠道供应链中的竞争,将零售商销售努力行为考虑在内,通过构建博弈模型分别研究了在集中决策模式和分散决策模式下,制造商与零售商的定价策略。研究发现,在集中决策模式下,线下零售渠道与线上直销渠道之间的价格差异随着两个渠道潜在需求量之间差异的增大而增大,并且两个渠道的最优价格分别与其市场潜在需求成正比。在分散决策模式下,两个渠道的最优价格亦与潜在需求成正比,并且线下零售渠道的最优价格随零售商销售努力程度的增加而增加,线上直销渠道的最优价格随着零售商销售努力程度的增加而减少。     

Cross-channel effects of omnichannel retail marketing strategies: A review of extant data-driven research

The authors review 50 empirical retailing research papers that have appeared over the last 20 years to take stock of what we know, need to know better, and do not know yet about within-retailer cross-channel effects of omnichannel retail marketing strategies on (a) consumer responses over their purchase journeys, i.e., online and/or offline search, purchase intention, frequency, amount, returns, loyalty, and (b) the retail firm's aggregate outcomes (e.g., sales, costs, profits, product returns) by channel and overall. Specifically, the authors focus on five strategies: (1) the addition of online channel by an offline retailer; (2) the addition (or subtraction) of offline channels by an online retailer; (3) addition of mobile shopping channel (website and/or app) by offline and/or online retailer; (4) cross-channel integration strategies; and (5) retail marketing mix strategies. The author/s integrate findings from empirical research on these strategies into a number of ‘insights’ about ‘what we know’. Prominent among these are the following: Adding a transactional online channel to an offline channel improves the retailer's overall sales even though offline channel sales can be cannibalized to some degree. Adding an offline channel by an online retailer, however, boosts online channel sales as well as overall sales of the retailer. Similarly, adding a mobile shopping channel usually increases customer purchase frequency and amount and overall sales of the retailer in the long-term. Strategies for greater cross-channel integration generally have a positive effect on a retailer's overall performance while online advertising has positive effects on offline channel consideration and sales as well as overall sales of a multichannel retailer. Other insights or findings that need further study or open questions are also identified. The paper closes with managerial implications of the derived empirical insights, and suggestions for future research.     

Customer Experience Management in Retailing: An Organizing Framework

Survival in today's economic climate and competitive retail environment requires more than just low prices and innovative products. To compete effectively, businesses must focus on the customer's shopping experience. To manage a customer's experience, retailers should understand what “customer experience” actually means. Customer experience includes every point of contact at which the customer interacts with the business, product, or service. Customer experience management represents a business strategy designed to manage the customer experience. It represents a strategy that results in a win-win value exchange between the retailer and its customers. This paper focuses on the role of macro factors in the retail environment and how they can shape customer experiences and behaviors. Several ways (e.g., promotion, price, merchandise, supply chain and location) to deliver a superior customer experience are identified which should result in higher customer satisfaction, more frequent shopping visits, larger wallet shares, and higher profits.     

How Online Product Reviews Affect Retail Sales: A Meta-analysis

A growing body of research has emerged on online product reviews and their ability to elicit performance outcomes desired by retailers; yet, a common understanding of the performance implications of online product reviews has eluded us. Scholars continue to navigate an array of studies assessing different design elements of online product reviews, and various research settings and data sources. We undertake a meta-analysis of 26 empirical studies yielding 443 sales elasticities to examine how these variables relate to retail sales. Building on well-established meta-analytical methods, we address the following questions: How does review valence influence the elasticity of retailer sales? What about review volume? For which product types and usage situations do online product reviews have a greater impact on retailer sales elasticity? Which types of online reviewers and websites exert the greatest influence on retailer sales elasticity? Our study answers these important questions and provides a much needed quantitative synthesis of this burgeoning stream of research.