Retail Store Image Research Articles

Evaluating retail store image - an empirical study in India

Retail industry in India is pivotal for its economy contributing around 20% to the country's gross domestic product. The competition is retaining and attracting new customers to the store. There are many tangible and intangible factors influencing the success of a store. Store image, which is formed by the stake holders encompassing all the components of retail mix play an important role in store success. The research is carried out in seven major cities in the eastern part of India. A structured questionnaire containing 32 items was developed based on literature review. A total of 552 usable responses were collected across different demographic profile for the study. The paper identifies eight factors influencing the store image viz. store reputation, physical characteristics, customer service, convenience, product reliability, supporting facilities, services, and pricing policy. It is found in the study, supporting facility has more influence on overall image of the store, followed by product reliability and services. It is also observed that pricing policy of the store has least impact on store image. In the emerging economic scenario Indian retailers shall be more scientific in their approach and give right importance to the parameters influencing their bottom line.

Relative importance of retail store image and consumers characteristics on the perception of value and willingness to pay a premium price

Retail store image, customer evaluation of merchandise value and intention to purchase have been studied as a most important constructsof the retail domain. It is considered from previous research, that store image is expressed in terms of tangible and intangibledimensions as assessed by consumers. Consumers are affected by the store’s attributes and consider image associations in order toassess perceived benefits and attitudes. This study develops a proposition that store image makes an influence on the level of perceivedproduct value. As recent research has shown, perceived value is related to willingness to pay a higher price. Accordingly, thisstudy posits a path model of store image, product value perception and willingness to pay a premium price. The proposed theoreticalframework entails insights on the differences in retail image – customer attitude relationship according to customer characteristics –gender and income. Therefore I hypothesize the impact of gender and income on the perceived merchandise value and willingnessto pay a premium price. Analyzing the path model, this paper investigates the influence of retail image and customer characteristicson the important retail outcomes. The results suggest a link of retail store image and perceived value of merchandise, also the hypothesizedassumptions of the link of customer income and endogenous variables of perceived value of merchandise and willingnessto pay a higher price were supported by the results. Findings of the structural model do not support the effect of the gender on therelationship between retail image and resultant variables of perceived value of merchandise and willingness to pay a higher price. KEY WORDS: retail store image, perceived value of merchandise, willingness to pay a higher price. DOI: http://dx.doi.org/ 10.15181/rfds.v9i1.602

Space Utilisation and Retail Store Image: How the Arrangement of Organic Foods Impacts on the Overall Image of Retail Stores

Marketing ZFP is a platform for the academic dialog between marketing science and marketing practice. It offers critical depictions of the newest developments in the central areas of marketing science and marketing practice. Thereby, Marketing ZFP dedicates itself particularly to the transfer of methodological knowledge into practice.

Consumer–retailer love and attachment: Antecedents and personality moderators

Because loyalty to services remains elusive and unpredictable, there is a need to study consumer relationships with firms apart from the established satisfaction–loyalty chain approach. To that end, the present paper investigates feelings of attachment and love through two empirical consumer studies of two different grocery retailer brands. The findings of the current study imply that retail store image, perceived transactional value, and corporate social responsibility (CSR) associations positively influence consumer–retailer love levels. Furthermore, we find that for consumers scoring low on the value of warm relationships with others and for consumers characterized by an avoidant attachment style, the effect of consumer–retailer love on re-patronage intentions is less salient. Interestingly, in the case of highly avoidant individuals, the effect of consumer–retailer love is negative. Managerial implications for building consumer-firm love in the context of grocery retail, as well as future research perspectives, are provided at the end of the paper.

An Investigation Of Selected Dimensions Of Retail Store Image: Bricks And Mortar Versus Online

Research examining the components of retail store image has focused on the most important features to customers. Merchandise return policy, an element of the Service dimension, has not been well researched. In the past decade the Internet has created another means to market products, and research relating to merchandise return policies for sales of Internet firms is virtually non-existent. This study compares the merchandise return policy in both bricks and mortar and Internet firms. Merchandise return policy appears to e a fertile area for future research.

Cultural influence on loyalty tendency and evaluation of retail store attributes

PurposeThe purpose of this paper is to examine the cultural influences on young consumers' loyalty tendency and evaluations of the relative importance of apparel retail store attributes in Taiwan and the USA.Design/methodology/approachA structured questionnaire was developed to collect the data. Factor analysis was employed to identify dimensions of apparel retail store image attributes. Pillai's Trace multivariate analysis of variance and hierarchical multiple regression analysis were used to examine the hypotheses.FindingsResults of the study showed that American consumers have significantly greater collectivistic characteristics than Taiwanese. The paper also found that country of residence is a significant and stronger indicator in predicting loyalty tendency than individualism and collectivism dimensions. The results of the study showed that evaluation of the relative importance of retail store attributes was influenced by culture. Among the five apparel retail store attribute dimensions identified in the study, Taiwanese and US respondents' evaluation of the importance of “convenience”, “product” and “information communication” factors of retail store image attributes differed significantly.Research limitations/implicationsThe paper may contribute to international retailers' understanding of the similarities and differences between Taiwanese and US markets and in determining the ideal components for these retailers to create an optimized apparel retail store image in two different countries' markets. The findings from the study could serve as an important benchmark for retailing strategy, helping retailers to effectively redesign their apparel stores to attract consumers in different markets and foster consumers' loyal to the company.Originality/valueDespite the growing internationalization of fashion retailing, this particular sector has attracted little research attention, and no research has been done to investigate the cultural differences of consumers' evaluations of apparel retail store image attributes.

Building store brands using store image differentiation

PurposeThe opening up of the Indian retail sector has seen a proliferation of the corporate players through different retail formats and stores – the majority being in the food and groceries. This necessitates creating, building, and managing differentiated retail store brands, and image differentiation, to attract and retain shoppers. This research paper attempts to understand whether the Indian consumers differentiate the various store brands and images based on their experiences.Design/methodology/approachThe study was conducted in two stages – list of parameters of evaluation of retail store image (developed from the literature), discussed with middle‐level managers from the retail sector to finalize parameters relevant for store image measurement in the Indian context and a questionnaire evolved for primary data collection, administered to 326 SEC A and B respondents (shoppers of food and grocery from modern retail stores). To assess the store image dimensions perceived by these shoppers, factor analysis was employed and for understanding various store image attributes used for differentiation of store brands one‐way analysis of variance was employed.FindingsResults reflect that Indian shoppers have started identifying the dimensions of retail store image and are differentiating the various stores on the basis of functional attributes. Eventually, the stores would have to create differentiation based on psychological attributes.Research limitations/implicationsThe paper is limited to the organised modern food and grocery retail stores of Ahmedabad city.Originality/valueThe paper can be helpful to Indian retail store chains to focus on elements to create a differentiated store image.

The Influence of Sustainable Development on Retail Store Image

This article explores young consumers’ perceptions of the sustainable development (SD) initiatives of French food retailers and evaluates their impact on the brand image of the retailers and their relationships with consumers. The methodology incorporated the analysis of the websites of the main French food retailers, a press review, eight in-depth interviews and a face-to-face survey. The findings highlight that young consumers tend to link SD more to ecology and less to social and economic issues. When a retailer’s SD actions are perceived and valued, young consumers show an emotional connection that is translated into positive attitudes, purchasing intentions and a willingness to recommend the retailer. When young consumers are not sensitive to SD actions, they continue to choose their retailer on the basis of geographical proximity. Five key dimensions seem to best describe brand image in relation to SD actions: Sympathy, Innovativeness, Human Touch, Responsibility and Opportunistic Behaviour. This last dimension is the only one with a negative connotation. This is because for some consumers, investments in SD are considered to be mostly driven by profit-seeking.

Segmentation of Shoppers using their Behavioral Patterns Based on Store Images

The main theme of this paper is to portray the segmentation of the shoppers based on their behavioural pattern towards the retail store images. Primarily, this article triggers off the various behavioural outcomes of the shoppers which have been influenced by the different store attributes. Based on the various store attributes, the shoppers have been segmented by the use of k-means Clustering Algorithm. The segment was well separated by using cluster validity function by Xie and Beni. The resulted segments are Pre-Determined, Variety-Seekers, Economy and Familiar. It has been found that every segment has its own impacts over the various store images and the managerial implications of these attributes have been highlighted.

Effects of Retail Store Image Attractiveness and Self-Evaluated Job Performance on Employee Retention

The purpose of this research was to investigate the effects of store image attractiveness and self-evaluated job performance on internal job satisfaction and organizational commitment. A total of 317 retail store employees at 8 regional malls in Arizona, Illinois, and Iowa completed a self-administered questionnaire. Employees who find the store’s image attractive and/or positively evaluate their job performance in the organization are likely to exhibit a high level of both internal job satisfaction and organizational commitment. Employees who are satisfied with and/or committed to their current job tend to be less likely to voluntarily leave from their current position which in turn, tends to increase employee retention in the store. In this way, turnover can be considered a positive occurrence for retailers because, if managed well, the better performing employees are likely to stay employed within the organization while, conversely, the poorer performing employees are more likely to leave. Although the relationships between store image attractiveness, self-evaluated job performance, internal job satisfaction, organizational commitment, and intention to leave have been examined in past research, the specific direct and indirect relationships examined in this study have not yet been previously investigated using a sample of retail sales associates.

Consumer-Retailer Emotional Attachment: Some Antecedents and Personality Moderators

Since loyalty in services remains elusive and unpredictable, there is need to study consumer relationships with firms apart from the established satisfaction-loyalty chain approach. To that end, the present paper focuses on feelings of attachment and love and investigates through two empirical consumer studies, in two different grocery retailer brands, (a) emotional attachment effects on re-patronage intentions, (b) predictors of emotional attachment and, (c) moderating effects of consumer traits’ on the (a) relationship presented above. The findings imply that perceived transactional value, retail store image and corporate social responsibility (CSR) associations determine consumer-retailer emotional attachment levels. Furthermore, we find that for consumers scoring low on the social value of warm relationships with others, and for consumers characterized by an avoidant attachment style, the effect of emotional attachment on re-patronage intentions is less salient. Interestingly, in the case of high avoidant individuals the effect is negative. Direct managerial implications for effectively manipulating consumer-firm emotional attachment in the context of grocery retailing as well as future research perspectives are provided at the end.

The influence of a retailer's corporate social responsibility program on re-conceptualizing store image

The construct of retail store image is typically built based on a variety of the store's functional attributes. This conceptualization fails to consider the role of corporate social responsibility (CSR) polices and practices in forming store image. Results from a study of 460 consumers indicate CSR influences consumer store image. CSR is particularly effective at influencing store image when the retailer experiences a positive performance perception among its customers. Consumers shopping at such stores are more receptive to CSR programs, and experience significant increases in their level of satisfaction and loyalty to the store through the addition of these programs.

Retail Image as Seen through Consumers' Eyes: Studying International Retail Image through Consumer Photographs of Stores

The aim of this article is to explore how retail store image is perceived by consumers from different cultural backgrounds and with different degrees of awareness and experience of the retailer. The subject is IKEA, a retailer recognized as having a global approach to the markets in which it operates, resulting in a highly standardized approach to store branding. However, rather than employing traditional methodologies to elicit consumer perceptions of store image, we attempt to capture consumer perceptions through interpretations of the visual images generated by the participants themselves. The photo-elicitation method employed captured the different interpretations and meanings attached to commonly identified elements of store image and reinforced the central role played by the store itself in retail image formation.

Food retail positioning strategy: a means‐end chain analysis

This research conducts a means‐end chain analysis of the food sector and explores the extent to which the findings made can be used to inform the retail positioning strategy of food retailers. Using means‐end theory as the theoretical underpinning of the study, the paper employs laddering methodology to identify the linkages between food retail store attributes and personal values. The findings of the paper present a more personally relevant representation of consumer’s perceptual orientations towards food retail store image. At the attribute level “good quality products”; “good reputation”; “store has additional services” and “value for money” are most sought after. These were linked to the consequences “feel good” and to “save time”. Overall, the findings support previous value driven research, concluding that “happiness” and “quality of life” are the most strived for personal values. Strategic implications for retailers are discussed and future research recommendations are made.

An exploratory investigation into e-tail image attributes important to repeat, internet savvy customers

This paper offers results from an exploratory study investigating e-tail store image attributes important to repeat, internet savvy customers of a major Australian grocery e-tailer. The study was undertaken in response to a perceived need on the part of the e-tailer for a better understanding of how image operated on-line, and a review of extant literature which indicated that while retail store image in traditional bricks-and-mortar environments had been extensively investigated; limited empirical work involving consumers had been undertaken within the e-tail environment. Three components incorporating traditional and e-tail specific attributes were identified; core demands, institutional factors and information.

A test of the stability of retail store image mapping based on multientity scaling data

Multientity scaling is a multiattribute measurement procedure that obtains ratings of two or more entities from a single respondent at the same time. The purpose of this research is to examine experimentally the stability of perceptual maps of retail stores based upon two types of multientity scaling data — data produced by attribute and entity-based scaling procedures. The findings indicate both procedures may produce mapping instability when the comparative retail store context of the ratings is changed, with attribute-based scaling being characterized by more instability than entity-based scaling. Based upon the findings, potential methods of increasing retail store image mapping stability are explored.

Retail store image: a means‐end approach

Retail store image has been shown to play an important role in store patronage, and it is widely accepted that psychological factors have a significant role in store image formation. Past research has often involved the measurement of tangible attributes, or links between store images and consumers’ self‐images. This study was undertaken to move to the next stage by exploring the link between perceived store image and the personal values which underlie behavioural choices. Fashion retailing was selected as an appropriate research domain because of the well‐established associations between clothing choice, personality, self concept, and personal values. Means‐end theory and laddering methodology were employed in interviews with 30 female respondents. The hedonic values of “enjoyment and happiness” and “quality of life” were found to be the terminal values most sought by consumers in association with store image. These were linked through the consequence “nice feeling” to the tangible attributes of “price”, “quality” and “reputation”. The study illustrates an application of means‐end methodology in a retail environment, and the results provide a platform for fashion store image and positioning strategies. Suggestions for further research are made.

The influence of brand recognition on retail store image

Investigates the relationship between brand characteristics ‐ awareness level and image ‐ and their influence on consumers’ perceptions of retail image. Proposes a model of relationships between the number of recognizable brands carried by a retail establishment, the presence/absence of an anchor brand, and perceptions of retail image. Presents the analysis and results of a study designed to test the model. In addition, develops and tests a measure of retail store image. Indicates that one tactic for ensuring a favorable retail store image is a merchandise mix composed of a relatively high number of brands possessing high brand awareness, and one or more brands with a strong brand image. Offers recommendations for both brand and retail managers.

A Comparative Analysis of Neural Networks and Statistical Methods for Predicting Consumer Choice

This paper presents a definitive description of neural network methodology and provides an evaluation of its advantages and disadvantages relative to statistical procedures. The development of this rich class of models was inspired by the neural architecture of the human brain. These models mathematically emulate the neurophysical structure and decision making of the human brain, and, from a statistical perspective, are closely related to generalized linear models. Artificial neural networks are, however, nonlinear and use a different estimation procedure (feed forward and back propagation) than is used in traditional statistical models (least squares or maximum likelihood). Additionally, neural network models do not require the same restrictive assumptions about the relationship between the independent variables and dependent variable(s). Consequently, these models have already been very successfully applied in many diverse disciplines, including biology, psychology, statistics, mathematics, business, insurance, and computer science. We propose that neural networks will prove to be a valuable tool for marketers concerned with predicting consumer choice. We will demonstrate that neural networks provide superior predictions regarding consumer decision processes. In the context of modeling consumer judgment and decision making, for example, neural network models can offer significant improvement over traditional statistical methods because of their ability to capture nonlinear relationships associated with the use of noncompensatory decision rules. Our analysis reveals that neural networks have great potential for improving model predictions in nonlinear decision contexts without sacrificing performance in linear decision contexts. This paper provides a detailed introduction to neural networks that is understandable to both the academic researcher and the practitioner. This exposition is intended to provide both the intuition and the rigorous mathematical models needed for successful applications. In particular, a step-by-step outline of how to use the models is provided along with a discussion of the strengths and weaknesses of the model. We also address the robustness of the neural network models and discuss how far wrong you might go using neural network models versus traditional statistical methods. Herein we report the results of two studies. The first is a numerical simulation comparing the ability of neural networks with discriminant analysis and logistic regression at predicting choices made by decision rules that vary in complexity. This includes simulations involving two noncompensatory decision rules and one compensatory decision rule that involves attribute thresholds. In particular, we test a variant of the satisficing rule used by Johnson et al. (Johnson, Eric J., Robert J. Meyer, Sanjoy Ghose. 1989. When choice models fail: Compensatory models in negatively correlated environments. J. Marketing Res. 26(August) 255–270.) that sets a lower bound threshold on all attribute values and a “latitude of acceptance” model that sets both a lower threshold and an upper threshold on attribute values, mimicking an “ideal point” model (Coombs and Avrunin [Coombs, Clyde H., George S. Avrunin. 1977. Single peaked functions and the theory of preference. Psych. Rev. 84 216–230.]). We also test a compensatory rule that equally weights attributes and judges the acceptability of an alternative based on the sum of its attribute values. Thus, the simulations include both a linear environment, in which traditional statistical models might be deemed appropriate, as well as a nonlinear environment where statistical models might not be appropriate. The complexity of the decision rules was varied to test for any potential degradation in model performance. For these simulated data it is shown that, in general, the neural network model outperforms the commonly used statistical procedures in terms of explained variance and out-of-sample predictive accuracy. An empirical study bridging the behavioral and statistical lines of research was also conducted. Here we examine the predictive relationship between retail store image variables and consumer patronage behavior. A direct comparison between a neural network model and the more commonly encountered techniques of discriminant analysis and factor analysis followed by logistic regression is presented. Again the results reveal that the neural network model outperformed the statistical procedures in terms of explained variance and out-of-sample predictive accuracy. We conclude that neural network models offer superior predictive capabilities over traditional statistical methods in predicting consumer choice in nonlinear and linear settings.

Memories of the way stores were and retail store image

Research shows that store image is an important component of a consumer’s store choice and use of a store environment. Most of this research ignores how store image might vary across different consumer segments. Examines the impact of age on final consumers’ perceptions of retail store image. Reveals that shopper age significantly affects perceptions of store image. Younger consumers feel more positive about both store characteristics and salesperson attributes than do older shoppers. Retailers employing store image research should be mindful of how the age of different consumers could affect their findings.