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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.

Using panel data on gasoline and grocery transactions in Korea, the purpose of this paper is to empirically explore the effect of a retail chain store’s establishment of on-site fuel sales. The empirical analyses present strong empirical evidence that the sale of fuel had statistically and economically significant effect on retail store traffic and revenue in the short run. However, the effect did not remain significant in the longer run. To explain the dramatic decrease in the effect of the fuel sale, the authors consider the enhanced competition in the local gasoline retail industry and examine cross-sectional price variations at the station level. The results suggest that the increased competition led to the reduction in the price dispersion across stations and thereby to an increase in consumer welfare.

Using a linear specification that has traditionally been used to model retail chain data, the authors developed a series of difference-in-differences models. This technique is ideal for estimating the effect of a treatment in the presence of possible selection bias and has been widely employed in many social-science studies on policy intervention.

In a certain environment, introducing fuel sales did not increase retail chain store traffic or revenue in the long run, despite having statistically and economically significant effects in the short run. The results document empirical evidence of myopic management in a common marketing practice, which often leads to a negative impact on the firm value in the long run.

The span of data and sample size were limited to meet the company’s data protection policy.

Considering that many of developed countries are characterized by a gasoline retail environment similar to that which is investigated in this paper, the authors believe that the implications of the results are particularly valid for practitioners and policy makers.

The findings document empirical evidence of myopic management in a common marketing practice, which often leads to a negative impact on the firm value in the long run. Marketing researchers should make efforts in establishing metrics to help identify myopic management decision.

This paper addresses an interesting and practical issue related to the effects of the introduction of gasoline sales by a supercenter store on its store traffic.

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.

The aim of this study is to develop and empirically test a theoretical model of competition between anchor and non‐anchor stores in a shopping mall. In doing so, the goals are to extend the literature on retail co‐location to account for effects of anchor stores' quality levels, and to explain an observed pattern of choices of anchor‐store quality levels made by mall developers.

This study uses a game‐theoretic approach to model the actions of mall developers, stores, and consumers in a competitive framework, then verifies the equilibrium predictions of this model using an empirical approach and a data set including all major malls in the US and Canada.

The key finding of both the analytical and empirical models is that there exists a positive and concave (i.e. reverse U‐shaped) relationship between anchor quality and mall size, i.e. that the highest‐quality malls are typically found in the middle range of mall sizes.

This study introduces a relatively basic framework that could be expanded to incorporate a more flexible variety of contract types between mall developers and tenants, as well as additional sources of consumer utility associated with a single visit to a mall.

This study provides mall developers with a basis for understanding the impact of anchor quality on competition between stores in a mall.

This study addresses a gap in both the analytical and empirical literature on determinants of mall traffic and profit, specifically pertaining to how these variables are affected by anchor stores and their quality levels.

Gives a definition of merchandising explaining how and why it works effectively. Discusses its power and cost‐effectiveness as a means of ensuring a final pre‐purchase exposure of consumers to persuasive or informative material. Investigates five merchandising techniques: manipulation of store traffic flow; shelf positioning; allocation of limited shelf space between competing claims; use of point‐of‐sale material; and special displays. Shows how these can be used profitably by the retailer and wholesaler. Presents a ten‐part plan for an organized approach to merchandising.

The purposes of this paper are to propose a different profitability metric (i.e. anchor category profits) at the category level based on the concept of anchor categories and to illustrate how such a metric can be calculated in field settings to offer a balanced view of profit structure from both the accounting and marketing perspectives.

First, the concept of anchor categories is developed drawing on anchor effects theory and automatic cognitive processing theory. Based on anchor categories, this paper proposes a formula for calculating anchor category profits. Using the data collected with a survey instrument, this paper calculates accounting profits and anchor category profits for two grocery stores.

The intra-store analysis of accounting profits and anchor category profits reveals that the two profit measures project different profit contribution patterns by product categories for each store. The inter-store analysis provides quite different, yet useful information about profit structures for the two grocery stores. Although the two stores are similar in terms of accounting profits, their anchor category profits show different pictures regarding profit contribution patters by product categories between the two stores, revealing that different categories attract customers to different stores.

Comparing accounting profits and anchor category profits allows retail managers to identify traffic generator categories and cash generator categories, which helps retail managers develop more effective category management to increase storewide profits.

This paper increases understanding of the relationship between product categories and store choice behavior by offering a theoretical rationale to explain why some product categories influence consumers’ store choice. This paper also proposes anchor category profits as a more implementation-friendly category-level profitability metric that combines accounting principles with consumers’ shopping trip planning behavior.

This study aims to propose a new method to predict retail store performance using publicly available satellite imagery data and machine learning (ML) algorithms. The goal is to provide manufacturers and other practitioners with a more accurate and objective way to assess potential channel members and mitigate information asymmetry in channel selection and negotiation.

The authors developed an open-source approach using publicly available Google satellite imagery and ML algorithms. A computer vision algorithm was used to count cars in store parking lots, and the data were processed with a CNN. Linear regression and various ML algorithms were used to estimate the relationship between parked cars and sales.

The relationship between parked cars and sales was nonlinear and dependent on the type of channel member. The best model, a Stacked Ensemble, showed that parking lot occupancy could accurately predict channel member performance.

The proposed approach offers manufacturers a low-cost and scalable solution to improve their channel member selection and performance assessment process. Using satellite imagery data can help balance the marketing channel planning process by reducing information asymmetry and providing a more objective way to assess potential partners.

This research is unique in proposing a method based on publicly available satellite imagery data to assess and predict channel member performance instead of forward-looking sales at the firm and industry levels like previous studies.

Increased competition among different retail formats has led mall managers to focus on mall promotional activities to attract shoppers to malls. The purpose of this paper is to understand Indian mall retailers views on mall events and its role in improving traffic, sales and mall image.

The current study used a qualitative to decipher mall retailers’ views regarding mall events. In total, 36 in-depth interviews of mall retailers across 13 metropolitan and non-metropolitan cities (Tier-I and Tier-II) were conducted to develop a comprehensive understanding of mall events organized by Indian mall managers.

The findings revealed that mall events were categorized under six different types: product launch events, events organized to promote the social cause, commemorate festivals, celebrity nights, events organized by retailers in malls and theme events. There were differences in the nature of events used by malls in bigger and smaller cities across India. The nature of mall events varied according to regional, cultural and lifestyle factors across the country.

Mall managers can use the insights from the study on mall events for segmenting and targeting strategies. The different types of mall events can be used for improving footfall, sales and mall image. The study findings employ a grounded theory approach to understand mall retailers’ views on mall events. Future research can be directed toward understanding mall managers’ and consumers’ opinions about the relevance of mall events in improving footfall and profitability of malls.

Extant research has looked at mall events, their role and efficacy in a consolidated manner. The current study attempts to segregate the events organized by mall management into distinct categories and provide linkages of these categories concerning mall image and traffic.

The purpose of this study is to examine customer orientation and fashion merchandising competencies to learn which strategic option has a stronger relationship with retailer financial performance.

A cross‐sectional survey was used to collect self‐report data from a random sample of 275 small specialty retailers of women's clothing in Bangkok. Retailers offer similar merchandise assortments and customer services in dense, highly competitive, agglomerative environments. The survey form contained multi‐item scales measuring customer orientation, fashion merchandising competencies, and store financial performance. Bivariate correlations, multiple regression coefficients, and hierarchical linear model coefficients describe relationships of interest, controlling for retailer location.

Results show medium to large effect sizes for several fashion merchandising competencies but no substantive effects for the two customer orientation constructs. Effect sizes depend on whether financial performance is measured subjectively or as retailer return on investment or as probability of retailer survival.

Data are restricted in range and reported effect sizes are smaller than true effect sizes. Data also are influenced by common method variance, influencing reported effect sizes in an opposite direction. Effect sizes may or may not describe causal relationships because of the study's cross‐sectional design. Because of the study's setting in Bangkok, results must be extended to similar retail settings with caution. Results indicate that a clustered fashion retailer can improve financial performance by striving for a fashion leadership position, anticipating fashion trends, and offering merchandise assortments in terms of styles and usages. Results indicate that a clustered fashion retailer will have difficulty improving financial performance via customer service and CRM activities.

Few studies in fashion retailing address predictors of financial performance at the individual store level. The authors help fill this knowledge gap by examining relationships between customer service activities, CRM activities, and key merchandising competencies and retailer subjective financial performance, return on investment, and probability of survival. Retailers compete in a spatially confined area, facilitating comparison shopping and heightening rivalries between retailers.

OUR leading article last month was headed “Automation or Extinction”. We were told, not directly (for whether through shyness or lack of conviction we know not, they never got in touch with us themselves) the TUC found no favour in it. Apparently while they don't mind us advocating shorter hours so that everybody who wants to can have at least a share in the employment that is available, they object to our underlining the fact that while Union chiefs wanted prices of their goods to be cut (in this case, steel; but the principle applies to everything) they neglected to say how this could be done.