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The study aims to investigate the impact of store flyer characteristics on store performance for different formats (hypermarket and supermarket) and customer segments (additional and regular shoppers). Specifically, the paper tests propositions on how flyer duration, variety of featured purchasing options, the category and brand mix on feature and the method used to communicate the deal price affect store traffic and sales.

Data were made available for analysis by a grocery chain that utilizes a hi-lo pricing strategy. To test the hypothesis a multiple linear regression analysis was used.

Results indicate that optimal store flyer configuration is related to the store format. Moreover, the response to flyer promotion programs varies across customer segments in relation to their degree of store loyalty.

Findings can assist marketers to develop more effective promotional strategies with regards to the bundle of promotions to be offered and the way they should be communicated. Future research should extend the analysis to other retailers and trading areas. Furthermore, it would be useful to replicate the analysis by separating the impact of in-store activities and store flyer effects.

This is the first attempt to analyse flyer impact on store performance for different formats and customer segments. Prior research is confined to supermarkets, although the enhancement of store traffic is related to format size. Moreover, the traffic and sales implications of store flyer composition have so far been analysed in an aggregate manner, disregarding customers' shopping patterns.

Describes the winning formula at Neiman Marcus that has made it the No. 1 luxury retailer in the United States in terms of sales per square foot and profitability. Highlights Neiman Marcus' efforts to define who its customers are and are not and to achieve superior focus on its customers by aligning location, price, service, and merchandise to fulfill these customers' every need. Describes ways in which Neiman Marcus prevents typical silo behavior between merchandising and selling and how it ensures that the right merchandise gets to the right customer, despite the challenge of doing this in 36 micromarkets.

To show how a company integrates two strong high-performance functions—merchandising and sales—to get the right merchandise to each customer in more than 30 diverse selling locations while consistently providing exceptional customer service.

Reviews the three sales forecasting models most commonly applied in retail site evaluation: multiple regression analysis; multiple discriminant analysis; gravity models. Discusses the important issues involved in the development and application of these methods – including their respective strengths and weaknesses. Key points are that there is no “black box” method and that in the real world of retailing the methods reduce, but do not remove, the need for practical, subjective analysis.

Describes a case study undertaken for a Chain company marketing durable goods rather than food products. Outlines the application of three techniques for assessing store attribute and sales performance. Attempts to report the potential and limitations of a statistical methodology in the business situation.

In this chapter, using a dual approach based on managerial and legal perspectives, we examine franchisee attitudes regarding online sales in franchise networks to better understand their views of the costs and benefits of e-commerce in a franchise network. We thus explore the following research questions from a franchisee perspective: What are franchisees’ attitudes regarding online sales?; Are online sales viewed as complementary or competing sales for physical stores?; What about the opening of a franchisor’s website?; and What about the opening of a franchisee’s website? We also analyze how several different e-commerce options available to franchisors impact franchisee incentives and how they would be treated under European Union competition law.

The empirical research is based on the conduction and analysis of 46 in-depth interviews with franchisees in the retail and service industries in the French market.

We find that online sales in franchise networks raise important questions for the franchisees, and for the franchisors as well. E-commerce has to be integrated into the development strategies of franchise networks. Franchisors should facilitate the online sales practices of their franchisees in order to avoid potential conflicts with them or among the franchisees themselves, thereby maintaining the control necessary to ensure healthy network growth. Moreover, franchisors should pay attention to the sharing of Internet sales with its franchisees.

Our chapter contributes to the stream of franchising literature dealing with the use of Internet in franchise networks. Moreover, it can be viewed by franchisors, franchise experts, franchisees, and franchisee candidates as an overview of issues linked to online sales in franchise networks. It also highlights best practices when having a multichannel strategy.

This study aims to analyze the impact of radio advertisements on urban commuters towards buying behaviour in retail stores and attempts to determine the role of radio advertising on dissemination of information on the sales promotions. The impact of radio advertisements on the store choice and buying preferences are analyzed based on empirical investigation.

This study is based on the empirical investigation of urban commuters who acquire information on sales promotion by listening radio advertisements during travel time. The sample respondents selected for the study frequently commute to their workplaces from the residential areas located in the southern, northern and suburban habitats in Mexico City. Data were collected by means of personal interviews during 2007‐2009 in different festival seasons broadly categorized as three seasons: April‐June (Spring sales following the occasions of Easter vacations, Mother's day and Father's day), July‐August (Summer sales) and November‐January (Winter sales following prolonged Christmas celebrations), when retailing firms including supermarkets, departmental stores and shopping malls advertise sales promotions frequently on radio.

The study reveals that shopping behaviour of urban consumer at retail stores in response to radio advertisements is highly influenced by the physical, cognitive and economic variables. Radio advertisements propagating promotional messages on sales of products have quick response to the supermarkets and department stores. Listeners of radio commercials are attracted towards advertisements, which are more entertaining while disseminating the message. This study on impact of radio advertisements on consumer behaviour revealed that advantage shopping at retail stores in response to radio advertisements is highly influenced by the physical, cognitive and economic variables.

A large number of people listen to radio while commuting in urban areas and respond to the broadcast of various commercial messages. There are limited studies available on radio advertisements and their socio‐economic impact. This study contributes to the existing literature on the subject.

This study examines the dynamic relationships of visit behavior in the multiple channels [personal computer (PC) and mobile channels] on online store sales performance.

The empirical data were from an online store for the period between August 14, 2015 and May 15, 2016. The data consisted of consumer visit behavior and online store sales performance. Vector autoregression with an exogenous variables model was adopted to investigate the dynamic relationships.

The empirical results show significant relationships between visit behavior metrics (number of visitors, average number of visits per visitor and average length of each visit) in the two channels and online store sales performance. The number of visitors through the PC and mobile channels strongly and positively affects online store sales performance both in the short term and in the longer term. Moreover, the number of visitors in the PC channel has the strongest influence on sales performance metrics, followed by the number of visitors and the average number of visits in the mobile channel. The PC channel's visit behavior metrics explain a larger proportion of the sales performance variance than that in the mobile channel.

The previous literature on consumer behavior in multichannel marketing mainly focuses on channel selection or migration, and examines the different factors affecting channel choice behavior. Little is known about the impacts of visit behavior in the multiple channels. This study adopts the heuristic-systematic information processing theory to unveil the impacts of visit behavior metrics in the PC and mobile channels on online store sales performance.

Weather is often referred as an uncontrollable factor, which influences customer’s buying decisions and causes the demand to move in any direction. Such a risk usually leads to loss to industries. However, only few research studies about weather and retail shopping are available in literature. The purpose of this paper is to develop a model and to analyze the relationship between weather and retail shopping behavior (i.e. store traffic and sales).

The data set for this research study is obtained from two food retail stores and a fashion retail store located in Lower Bavaria, Germany. All these three retail stores are in same geographical location. The weather data set was provided by a German weather service agency and is from a weather station nearer to the retail stores under study. The analysis for the study was drawn using multiple linear regression with autoregressive elements (MLR-AR). The estimated coefficients of weather variables using MLR-AR model represent corresponding weather impacts on the store traffic and the sales.

The snowfall has a significant effect on the store traffic and the sales in both food and fashion retail stores. In food retail store, the risk due to snowfall varies depending on the location of stores. There are also significant lagging effects of snowfall in the fashion retail store. However, the rainfall has a significant effect only on the store traffic in the food retail stores. In addition to these effects, the sales in the fashion retail store are highly affected by the temperature deviation.

Limitations in availability of data for the weather variables and other demand influencing factors (e.g. promotion, tourism, online shopping, demography of customers, etc.) may reduce efficiency of the proposed MLR-AR model. In spite of these limitations, this study can be able to quantify the effects of weather variables on the store traffic and the sales.

This study contributes to the field of retail distribution by providing significant evidence of relationship between weather and retail business. Unlike previous studies, the proposed model tries to consider autocorrelation property, main and interaction effects between weather variables, temperature deviation and lagging effects of snowfall on the store traffic or the sales. The estimated weather impacts from this model can act as a reliable tool for retailers to explain the importance of different non-catastrophic weather events.

Effective inventory management is critical to retailing success. Surprisingly, there is little published empirical research examining relationships between retail inventory, sales and customer service. Based on a survey of 101 chain store units, this paper develops and tests a series of hypotheses about retail inventory. Seventy‐five percent of the store owners/managers responded to the mail survey. As expected, significant positive relationships were found between inventory, service and sales. Specifically, support was found for the theory that inventory is a function of the square root of sales. Also, greater product variety leads to higher inventory, and service level is an exponential function of inventory. Finally, demand uncertainty was found to have no apparent effect on inventory levels.