Store Manager–Store Performance Relationship: A Research Note

Despite the critical role that store managers play in linking top management teams and service/retail employees, as well as in fulfilling corporate strategy within chain store environments, service management research infrequently addresses the factors that may promote store managers’ effective exchange relationships within the firm and subsequent effects on store operations and profitability. This study focuses on how store managers’ performance orientation, trust of a regional manager’s capabilities, and organizational commitment affect a manager’s relationships relative to regional managers and frontline employees. The direct effect of store managers’ relationship capacity on store performance is also examined. The results, based on survey data from managers of stores of a retail and service chain and company financial reports, generally support the suggested hypotheses. Specifically, a store manager’s relationship with his/her supervisor has a strong influence on how the manager views the supervisor’s leadership support and leadership style, which ultimately influence store performance (primary goods/service sales and store profits).     

Understanding Retail Managers’ Role in the Sales of Products and Services

This research investigates the influence of retail chain-level activities (e.g., district supervisor directives and policies) and store manager behaviors on the sale of physical products versus services. Using data gathered within a U.S.-based retail automotive parts chain, the authors discover that to sell services, especially in competitive environments, store managers should focus on sales planning and transformative leadership behaviors, which accentuate both the long-term planning horizon and the effects of managerial actions. In less competitive environments though, a more transactional approach (e.g., selling orientation) can be effective for selling services. Alternatively, to sell products, store managers’ selling effort appears to be the most important driver of success, and a transformative leadership approach may be detrimental when the retailer faces a high level of direct competition. In total, the findings suggest that corporate chain activities, such as the level and clarity of store managers’ goals and supervisor monitoring, influence store manager behaviors, which in turn affect the sale of physical products and services.     

Sales employees’ polychronicity and sales-service ambidexterity: Mediation of work engagement and moderation of store manager support

Sales employees are encountered with increasing job demands and volatile changes in the retail environment. In particular, the adoption of smart technologies in the retail sector has pressurized sales employees to be versatile and agile in the new marketplace. In this sense, performing multiple tasks within a limited time frame has become an important quality required for sales employees. Grounded in the job demands-resources model, we proposed that sales employees’ individualized resource (i.e., polychronicity) would be positively related to their sales-service ambidexterity though work engagement. We further posited that an organizational resource (i.e., store manager support) synergistically interacted with polychronicity to predict work engagement and subsequent sales–service ambidexterity. To test propositions, we collected multilevel data from 292 sales employees in 43 home-furnishing stores in India. Results demonstrated that the positive association among work engagement, polychronicity, and sales–service ambidexterity was more pronounced when store manager support was high than when it was low. These findings offer implications to overcome challenges faced by retail stores by indicating factors predicting sales–service ambidexterity in retail.     

Prices and promotions in U.S. retail markets

We provide generalizable results on the price and promotion tactics employed in the U.S. retail grocery industry. First, we document a large degree of price dispersion for UPCs and brands across stores, both nationally and at the local market level. Base price differences across stores and price promotions contribute to the overall price variance, and we show how to decompose the price variance into base price and promotion components. Second, we document that a large percentage of the variation in prices and promotion tactics across stores can be explained by retail chain and especially market/chain factors, whereas market factors explain only smaller percentage of the variation. Third, we show that the chain-level price and promotions similarity can be explained by similarity in demand. In particular, a large percentage of the variance in price elasticities and promotion effects can be explained by retail chain and especially market/retail chain factors. Further, price elasticities and promotion effects across stores of the same chain are hard to distinguish from the chain-market-level mean, and cross-price elasticities are typically imprecisely estimated. These findings suggest that retail managers may plausibly consider price discrimination across stores to be infeasible.

     

Estimation of product category sales responsiveness to allocated shelf space

A retail chain manager must draw on experience based on data available from his points of sale to diagnose space misallocations in stores and to make recommendations. This paper presents an empirical estimate of shelf space elasticities from a variety store chain database at product category level with a share of space vs. share of sales econometric model. It suggests that external influences could explain space elasticity differences. Results show that space elasticities increase with the impulse buying rate of the product category and do not depend on the type of store.     

“One-deal-fits-all?” On Category Sales Promotion Effectiveness in Smaller versus Larger Supermarkets

Even within a store chain and format, supermarket outlets often exhibit substantial differences in selling surface. For chain managers, this raises the issue of correctly anticipating the promotion lift, and of profitably managing promotion activities, across these outlets. In this paper, we conceptualize why and how store size influences the category sales effectiveness of four promotional indicators (depth of the promotional discount, display support, feature support, and whether the promotion is quantity-based). We then estimate the net moderating effect on four product categories for 103 store outlets belonging to four chains. For each of the promotion instruments, we find the percentage sales increases to be lower in large stores. For instance, whereas a 10% point increase in feature activity enhances category sales by about 1.64% in a 700 m² store, this figure drops to only 1.03% in a 1300 m² store – a 59% reduction. This moderating effect is especially pronounced for discount depth, the relative sales lift from a typical price cut being about 78% lower in the larger-sized outlet. However, since large outlets also have larger base sales, the picture changes when we consider absolute sales effects. The net outcome is that deeper discounts or quantity-based promotions do not systematically generate larger or smaller absolute sales bumps in large stores, whereas for in-store displays and features, we obtain a clear positive (be it less than proportional) link between store size and absolute category sales lift. When it comes to margin implications, we show that large stores gain higher profit from price cuts than small outlets only as long as the retailer keeps part of the manufacturer discount to himself. Managers can use these insights to improve their promotional forecasts across outlets, as well as to tailor their mix of instruments to store selling surface.     

Estimating the Impact of Displays and Other Merchandising Support on Retail Brand Sales: Partial Pooling with Examples

With the advent of scanning data, methodological issues have arisen, in particular as they relate to the reliability of parameter estimates in regression models. This study deals with the reliability of the coefficients of promotion-type dummy variables (e.g., display, leaflet, bonus pack,). Due to a lack of passthrough of trade deals to the end consumer, those coefficients can be typically unidentified or unstable when estimated at the store level and even at the chain level. Assuming that the individual-level coefficients of the dummy variables are draws from a common but arbitrary distribution, the authors suggest to "pool" the data for those variables (partial "pooling") across stores and across chains. They show with three real-life examples the increased reliability (with a correct sign) of the "pooled" coefficients as compared with the store-level or chain-level individual coefficients.     

The influence of social capital on local retail patronage in an urban setting

Local retail stores are currently facing intense competition from both online retailers and large chain stores. An understanding of local retail store patronage (i.e., patronage of retail stores in one's own community) is essential to the survival and growth of local retailers. Drawing on Social Capital Theory, we theorize and show with store-level survey data the influence of social capital (community attachment and reciprocity) on local retail store patronage in a large urban setting. We find that the impact of social factors differs for residents within the community compared to those outside of the community. We also demonstrate the importance of social factors in comparison to non-social factors. These findings contribute to the literature by extending the impact of social capital on local retail store patronage beyond rural settings, providing insight into urban consumers' decision to patronize local retail stores, and highlighting the impact of community boundaries. These findings also generate practical recommendations for local merchants and stress the importance of building reciprocal relationships with local customers as well as varying communications across community boundaries.     

Cross-category sales promotion effects

We introduce a multivariate binomial logit model measuring cross-category dependence and sales promotion effects of a retail assortment. This model requires as data both the market baskets of individual shoppers and the categories currently promoted in a retail outlet. A special section describes the stepwise procedure used to estimate parameters of this model. Its application is demonstrated analyzing 6147 purchases that were acquired in a medium-sized supermarket. We finally discuss the managerial relevance of this model for sales promotion decisions of retail firms.     

Open all hours: spatiotemporal fluctuations in U.K. grocery store sales and catchment area demand

Conventional population estimates do not account for spatiotemporal fluctuations in populations over a diurnal timescale at the level of retail store catchments. This presents challenges for the retail location-based decision making process which seeks to predict sales volumes and their temporal characteristics prior to new store construction. We present a novel analysis of the temporal fluctuations of store sales, evidencing links between the spatiotemporal distribution of specific population subgroups and temporal store sales. Previous research linking spatiotemporal populations and store sales is limited owing to the fact that commercial data are not openly available to academic research. However, this research has unprecedented access to store level temporal sales data and an established loyalty card scheme from a major UK grocery retailer making these analyses possible for the first time. Additionally, we demonstrate that current store classifications were inadequate for grouping stores with similar sales profiles and propose four new clusters of stores based on the times of the day that they generate revenues. This development has clear academic and commercial benefits, aiding our understanding of consumer behaviours and a novel solution for improved location modelling. We lay the foundations for further research building spatiotemporal demand fluctuations into retail location models.     

The impact of a gasoline crisis on retail sales

The gasoline crises of the 1970s demonstrated the need for including gasoline prices and gasoline shortages in models explaining retail sales. In this article, a model is constructed that incorporates the aforementioned variables, other variables, and a lagged sales figure as independent variable. The results indicate a high degree of explanatory power in predicting retail sales for a specialty store chain with a preponderance of their stores in large regional malls that sell a product which lends itself to unplanned purchase behaviour.     

Managing heritage brands: A study of the sacralization of heritage stores in the luxury industry

We investigate the concept of the heritage store, that is, the locations that lies at the heart of a brand׳s identity and history. Based on store observations and interviews with managers and sales personnel in the luxury industry, we analyze the characteristics of heritage stores and their role in the management of heritage brands. We show how managers sacralize a store׳s heritage to nurture the value proposition of the brand. Our analysis yields new insights into retailing, introducing the concept of the heritage store and emphasizing its sacralizalization. We outline the implications for retail marketing in developing and maintaining the sacralization of heritage stores.     

Evaluating store location and department composition based on spatial heterogeneity in sales potential

In this paper, we extend a retail location evaluation model with the possibility to include the effect of department size adaptation at the store level. We relate department-level store sales to a store's competitive and demographic environment, thereby providing richer insights into the drivers of department sales than a model of just aggregate sales. Further, we accommodate heterogeneity in consumer characteristics over space by using zip code level data and unobserved spatial effects in department sales by including spatially autocorrelated error terms.Using spatial panel data for 30 clothing stores belonging to one Dutch retail chain, we demonstrate how to use the modeling approach to analyze and predict sales performance of new and existing stores. We show that the predictive performance of our model is superior to that of a benchmark model that does not include spatial autocorrelation.     

The Showrooming Phenomenon: It's More than Just About Price

This paper examines the factors that influence competitive showrooming, whereby consumers visit an offline retail store to gather information but make their purchase online at a competing retailer. We survey 556 respondents to study how the benefits and costs of showrooming influence the consumer's decision to showroom. Not surprisingly, we find that expected average price savings from showrooming are positively associated with showrooming. In addition, however, the perceived dispersion in online prices is also positively related to showrooming. Moreover, we find that non-price factors play a key role in consumers' showrooming decisions: perceived gains in the quality of the product purchased when showrooming (measured as the fit with a consumer's need) and waiting time for service in the brick-and-mortar store are positively associated with showrooming. Online search costs are negatively related to showrooming. Time pressure that consumers face when shopping is negatively associated with their propensity to showroom. We discuss implications for researchers and retail managers. For example, managers of offline retail stores can curtail showrooming by increasing the number of sales personnel available in-store instead of providing currently employed personnel with more training. To encourage showrooming, managers of online retailers should make it easier for the customer to search online.     

Perceptual differences regarding leadership between the store manager and employees and its impact on frontline sales performance: A research note

This study focuses on the bright side of perceptual differences regarding leadership that may exist between managers and employees. Specifically, building on leadership literature, the authors propose that in situations wherein a manager’s perceptions of their own leadership are lower than that of their employees’ perceptions of their managers’ leadership, employees’ sales performance levels are higher. Data were collected from retail store managers and frontline employees in Brazil in three different contexts (e.g., footwear, clothing, and furniture). Based on polynomial regression analyses, the findings suggest that sales performance is generally higher when a manager’s self-perceptions are lower than their frontline employees’ perceptions of managers’ transactional and transformational leadership.     

A Bayesian multivariate Poisson regression model of cross-category store brand purchasing behavior

The availability of cross-category transaction data in the retailing industry has enabled the investigation of interdependence in consumer purchase behavior across product categories. In this paper, we develop a multivariate count model to uncover and predict the pattern of cross-category store brand purchasing behavior. The proposed multivariate Poisson regression model, which we estimate using a Bayesian approach, provides flexibility in capturing cross-category correlations for sparse multivariate purchase data associated with infrequently purchased categories or purchasing in retail outlets such as warehouse clubs. We compare the goodness-of-fit of the proposed Poisson regression model with alternate benchmark models using customer purchase records across five product categories from a national warehouse club and find that the proposed model provides a superior fit. We also carry out a profitability analysis to illustrate the use of the model in planning cross-promotions.     

A Decision Model for E-commerce-enabled Partial Market Exit

Struggling retail chains often try to recover profitability by closing some of their stores. The challenge in this strategy lies in determining how many stores to close, as store exit has implications for both the customers and the supply chain. After a store closes, its customers are lost forever to the competition, unless there is a surviving open store nearby or an electronic alternative such as an e-store. From the supply chain perspective, after a store closes, its supporting regional distribution center is left with less business, and thus reduced viability. This paper develops a decision support model to study the profitability of alternative retail network structures by varying the proportion of stores that are closed, the average price sensitivity of demand, the price difference between the online store and the traditional retailers, and customer retention rates.     

The different faces of coupon elasticity

Coupons account for over two-thirds of all consumer promotional efforts initiated by the manufacturers of consumer goods. In this study, the impact of coupons on brand sales is investigated and how that impact decays over the life of the coupon is demonstrated. Specifically, we present an econometric model that can capture coupon effects in terms of equivalent price reduction, account for coupon effects over time, allow inference of coupon effects when retailers decide to double or triple the coupon value, and provide both self-coupon and cross-coupon elasticities at different levels of aggregation. A widely used sales response model is adapted, and an analytical model is proposed to estimate both the self-coupon and cross-coupon (face value) elasticities of sales at the store level. From the store-level elasticity estimates for a given week, the authors analytically derive the coupon elasticities for the chain level by aggregating across stores, and over the life of the coupon by aggregating over time. The proposed sales response model is estimated with the data obtained from three markets for various product categories, and the coupon elasticities are computed. The proposed framework allows one to demonstrate the hypothetical equivalence of a shelf-price reduction for a given coupon face value in each week. Also, the effect of doubling the face value of a coupon results in more than a proportionate increase in elasticity. The authors find that both self and cross-coupon elasticities are much smaller in magnitude than the average self and cross-price elasticity measures reported in the literature.     

Retailing strategy for customer growth and new customer attraction

The image that current and potential customers have of a retail store affects the magnitude of patronage at that store. In attempting to increase store patronage, management of a retail store must look to people who already are customers, as well as to people who are not current customers. The appropriate strategy depends upon the dimensions used by people in their evaluation of the store. The hypothesis is tested that the strategy used for gaining increased patronage from customers may have to differ from that used to gain patronage from noncustomers.Field survey techniques were used to collect data from 225 adult females. Respondents evaluated three large retail department stores, which were believed to have distinct images in the minds of female shoppers, on the basis of a set of 12 semantic scales that represented various store attributes. Each respondent indicated frequency of shopping at each store. The data were analyzed by two different multiple discriminant analyses. For the customer growth strategy, the semantic scale measures were used to develop a discriminant model for each store to determine which attributes would be the best predictors of shopping frequency. The analysis relevant to the strategy of new customer attraction differed. First, shoppers were classified as loyal to one store on the basis of their rates of shopping at each store. Second, the 36 attribute measurements (12 scales for 3 stores) were factor analyzed, and three factors were extracted. Those attributes which loaded highest on each of the factors for each store were used as predictor variables in the discriminant analysis.The results of this study indicate that different marketing strategies may be required for increasing sales to existing customers and attracting new customers. In addition, consumers do not necessarily differentiate similar type retail stores on the same dimension.     

Statistical Inference Using Stochastic Switching Models for the Discrimination of Unobserved Display Promotion from POS Data

The execution of price and/or display promotion has a significant effect on the sales of a brand sold in a supermarket. Information on price and/or sales is available from POS data. However, unless an investigator collects information on the execution of display promotions from every retail store, such information is unavailable. This paper presents a method of identifying whether display promotion has been executed without having to visit individual stores. We treat the execution/non-execution of a display promotion as a state variable. An unknown stationary probability matrix is assumed to describe the probability of a transition between states. Each state is characterized by a different stationary time series model with unknown parameters. The objective of the analysis is to identify the model and to assign a probability model for each state at each time instant. Finally, we provide a high precision estimator of a past execution/non-execution of a display promotion based on the proposed model.