Retail Environment Research Articles

MCI모형을 이용한 중국 옌타이시 대형소매점 매출예측 및 상권영향분석

Recent research on GIS analysis, spatial interaction models, and site selection for large retail stores is actively underway in China both domestically and internationally. However, most studies tend to rely on secondary data provided by government agencies, neglecting research based on actual consumer survey data. Therefore, this study aimed to improve methods for analyzing commercial areas of large-scale retail stores in China by proposing the use of consumer data to enhance existing spatial interaction models. Specifically, by conducting surveys among consumers who actually visit large-scale retail stores, basic data such as store visit rates and visitor travel distances were collected to construct the MCI model. Through this approach, the study estimated the visit probability and market share of large-scale retail stores, and analyzed the impact of market environmental changes on commercial areas. Firstly, based on address data from 279 Chinese consumers, the study area was divided into 44 regions. These regions were combined with information on consumer shopping patterns and store details to construct a matrix of interactions between regions and large-scale retail stores. Secondly, important parameters in the MCI model, such as store attractiveness index and distance sensitivity, were estimated through OLS regression analysis. Findings revealed that the store type (regional large-scale retail, urban large-scale retail) did not significantly impact on consumers’ store preferences. Instead, customer visits exhibited an inverse relationship with distance and a direct relationship with store size. These estimated results were consistent with the theoretical perspectives of spatial interaction models. Thirdly, to examine how changes in the retail environment may affect retail businesses within commercial areas, the study focused on changes in sales and market share of surrounding retail businesses when a specific store expanded its area or entered a new region. The results showed that both expanding store area and entering new regions had negative impacts on other existing stores.

Scalable Microservices Architecture: Leadership Approaches for High-Performance Retail Systems

The rapid evolution of retail systems in the digital age necessitates the adoption of scalable microservices architectures to meet the demands of high-performance and responsive platforms. As the retail sector increasingly relies on technology to drive customer engagement, operational efficiency, and competitive advantage, the role of leadership in designing and implementing scalable microservices architectures becomes critical. This paper explores leadership approaches that are essential for guiding the successful deployment of microservices in high-performance retail systems. The shift from monolithic to microservices architectures represents a fundamental change in how retail systems are built and maintained. Microservices, characterized by their modularity, independence, and scalability, offer significant advantages over traditional monolithic architectures, particularly in handling the dynamic demands of modern retail environments. However, the successful implementation of microservices requires more than just technical expertise; it demands strategic leadership that understands the complexities of system design, cross-functional collaboration, and long-term maintenance.

Cross-cultural differences in the effects of the ambient scent on in-store behavior: the role of companionship

While previous studies have examined the influence of store atmospherics and social factors independently, limited research has investigated their synergistic impacts across cultures. In particular, the interactions between ambient scents, companionship influences, and cross-cultural shopping customs remain underexplored. Therefore, this study investigates how ambient scents influence retail shopping behaviors with a companion across cultures. Data were collected via surveys administered to customers in Polish and Indian shopping malls (N = 579), examining the impact of detected fragrances on time spent, money spent, purchase decisions, cognitive responses, and attitudes. Shopping with a companion in a scented environment has a more positive influence on time spent, money spent and impulse purchases in India than in Poland. There is no difference between these two cultures regarding cognitive responses to a scented retail environment, but there are significant differences for attitudinal responses and repurchase intentions. We found a positive association between the consumer rating of the shopping environment in terms of the ambient scent and the amount of money spent in India, but not in Poland. Theoretical and practical implications are discussed for optimizing atmospheric design according to cultural customs around shopping companionships.

Sale of second-hand goods by consumers: mediating role of satisfaction between perceived value and behavioural intentions

ABSTRACT Sustainable retail strategies are promoting product reuse and recycling, and the current trend of shifting retail environment in a socially and ecologically conscious market requires understanding second-hand merchandise transactions. The present study on second-hand product sellers examines perceived value and their effects on satisfaction (mediator) and behavioural intentions. The results show that economic, social, emotional, relational, and moral/ethical values are unrelated to satisfaction and behavioural intentions. While popular and well-regarded Expectancy-Disconfirmation theory underpinning hypotheses contradict the findings, thus, concluded that differential consumers-to-consumer behaviour intentions exists while selling or purchasing second-hands goods vs. new products. The research contributes by empirically testing additional theoretical linkages of perceived value with satisfaction and behavioural intentions relationship in the context of the second-hand goods market.

Smart technologies for retailing: who, what, where and why

PurposeThe retail landscape is dramatically changing due to a series of socio-economic and technological challenges, which can be faced through the adoption of smart technologies. Accordingly, a significant number of publications in this field have been produced, albeit with fragmented results. Therefore, this paper aims at both providing a clear and organised overview of the main smart technologies for physical retailing, in terms of application fields and expected impact, while identifying the major shortcomings and future research avenues.Design/methodology/approachThe research conducts a systematic review of the literature concerning the assimilation of smart technologies within physical retail environments, resulting in the analysis of 103 papers published from 2005 to 2023. The review highlights (1) the main smart technologies employed in retail stores, (2) their application area and (3) the beneficiaries of their adoption. Accordingly, these three aspects are initially assessed independently and then examined in combination.FindingsThe analysis presents a comprehensive list of 16 key technologies (what) that can support a wide range of processes, spanning from back-end functions to front-end activities, also enabling the connection with online channels (where), catering several and different benefits (why) to both customers and retailers (who). Besides, the research points out many uncovered topics that could be addressed by the academic community.Originality/valueTo the best of the authors’ knowledge, the review is the first one in the literature offering a thorough and organised overview of the different available technologies for in-store application and their impact on physical retail processes.

Review on Location of Fresh Cold Chain Logistics Distribution Center

This paper reviews the research status, existing problems and challenges, and future research directions of the location of fresh cold chain logistics distribution centers. The research background is based on factors such as the development of the fresh product market, the technological progress of cold chain logistics, the requirements of environmental protection and sustainable development, and the intensification of market competition. The significance of site selection includes improving transportation efficiency, reducing costs, improving customer satisfaction, optimizing supply chain networks, and achieving environmental sustainability.The former focuses on low-carbon, demand uncertainty, and competitive distribution center location, while the latter focuses on the new retail environment and cold chain distribution. The review of relevant literature points out that some progress has been made in the research, but there are challenges such as market demand uncertainty, incomplete data and limited model applicability.Future research directions include the location model of cold chain logistics distribution center based on big data, the location model considering sustainable development factors, and the location method of cold chain logistics distribution center integrating multi-index evaluation.In the conclusion, it is pointed out that in the past, the time window and the overall logistics network were rarely used as research evaluation indicators in the site selection problems, and the cost of reverse logistics and closed-loop supply chain was rarely considered. In the prospect part, it is proposed that in the future, we should pay attention to the problems of reverse logistics and closed-loop supply chain in the distribution of fresh agricultural products, consider the multi-objective optimization of low-carbon cold chain logistics network in different policies and fields, and combine full simulation technology and optimization technology to realize the system optimization research.

Retail Environment and Hair Styling Exposure Study

Retail Environment and Hair Styling Exposure Study

Heritage elements and Artificial Intelligence as storytelling tools for virtual retail environments

In the rapidly evolving landscape of technology, the metaverse has emerged as a groundbreaking platform for redefining fashion presentation, experience, and conceptualization. This paper investigates the interplay between fashion and Virtual Reality (VR) through specific use cases of virtual showrooms. Each case highlights the metaverse's potential in fashion, from reproposing historical elements to expressing contemporary trends, showcasing technological innovations, like Artificial Intelligence (AI), and user engagement strategies. This analysis shows how such commercial spaces can be exploratory platforms for narrating a brand's history and heritage elements, revealing VR's potential to enhance user engagement with immersive 3D environments and dynamic narratives. The paper further investigates advancements in integrating heritage with e-commerce elements and using heritage and AI as storytelling tools, concentrating on four exemplary projects. This integration suggests a future of increasingly immersive, personalized, and interactive experiences, marking a new chapter in how fashion is conceived, presented, and experienced.

Identifying the drivers of ‘loyal showrooming’: a systematic literature review

ABSTRACT Retail showrooming behaviour is described as the phenomenon in which customers browse the products in-store before making the purchase online at a lower price. This is due to the fact that different shopping channels have emerged and have gained the attention of customers. However, customers do prefer visiting the showroom to check on the prices and best buying options within the store. The retail environment is progressing towards the environment where store-based offline shopping does exist with online shopping mediums, and retailers need to understand the factors that maximize customers’ purchase within the store during showrooming. This paper is aimed at establishing the significance of loyal showrooming and determining its drivers based on an extensive literature review of 168 research articles published in indexed journals during the last 12 years. It is suggested that retailers should adopt strategies based on the present multichannel retailing environment and the driving factors identified to convert the showroomers into loyal showroomers.

An Analysis of Consumer Behaviour in Multichannel Retailing and Omnichannel Retailing

This paper investigates consumer behavior in multichannel and omnichannel retailing environments. With the evolution of technology and the increasing importance of the internet, consumer expectations and shopping behaviors have significantly transformed. Multichannel retailing, which involves using multiple channels for selling products, and omnichannel retailing, which ensures a seamless consumer experience across all channels, have emerged as critical strategies for businesses. This study aims to explore the differences in consumer behavior in these two retailing models, examining factors such as customer satisfaction, purchase frequency, and loyalty.

Impulse Buying Behavior in E-Commerce: Factors Influencing Spontaneous Purchases in Online Retail Environments.

Impulse Buying Behavior in E-Commerce: Factors Influencing Spontaneous Purchases in Online Retail Environments.

Correlation Among Neighborhood-level Measures of the Tobacco Retail Environment.

Tobacco retailer density and distance to tobacco retailers are understood to influence tobacco-related behaviors; however, there is no general agreement on how to best characterize or measure the tobacco retail environment (TRE). In this data-driven analysis, we examine similarities among neighborhood-level measures of the TRE and assess how geographic resolution of the neighborhood units may affect them. We used locations of likely tobacco retailers in the United States (US) to calculate multiple retailer count, density, and distance measures. Measures were calculated at the Census block group, tract, and county (including county equivalents) levels of geographic aggregation. Spearman's correlation was used to evaluate similarity among the TRE measures. At the block group and tract level, correlation among all TRE measures ranged from slightly negative (ρ = -0.03) to nearly perfect (ρ = 0.99). At both levels of aggregation, distance-based TRE measures were highly correlated (ρ > 0.76). At the block group level, simple count of retailers was highly correlated with the density measures (ρ > 0.83), and at the tract level, simple count was moderately to highly correlated with the density measures (ρ > 0.5). Findings were generally similar at the county level; a notable deviation was that retailers per person was negatively correlated with all other TRE measures (range from ρ = -0.08 to ρ = -0.32). Some common measures were not correlated, suggesting they capture different aspects of the TRE; similarity among the various measures also varied by level of geographic aggregation. Because the tobacco retail environment shapes people's tobacco-related behaviors, using appropriate measures to characterize it at a neighborhood-level is paramount. Our work highlights both the similarities and differences among a set of common measures, thereby suggesting the measures may be capturing different aspects of the overall retail environment. Our findings regarding geographic level of aggregation underscore the importance of neighborhood definition in any tobacco retail environment analysis.

From communal places to comfort zones: Familiar stranger encounters in everyday life as a form of belonging

Familiar strangers, individuals who are visually recognisable yet do not engage in verbal conversations, emerge in communal urban places on the way and in between regular daily activities in the home and workplace. Described as invisible social ties and light touch community, familiar strangers represent an understudied and untapped source of sociality that offer promise by way of an antidote to the global increase in reports of loneliness. In this study, we examine the extent to which familiar stranger encounters in communal everyday places might act as an important source of social identity, belonging and perceived attachment. We estimate regression models using data from a 2022 intercept survey of 278 residents in Brisbane, Australia conducted in situ at public parks, transit stations, retail environments, and thoroughfares to estimate the influence of familiar strangers and frequency of visitation on sense of belonging and place attachment. Our results show belonging emerges through familiar stranger encounters in everyday communal places outside of the residential neighbourhood and suggest that coupling urban design features that enhance visible proximity with scheduling that encourages repeated, synchronised visitation can contribute to bounded communities of belonging at everyday communal places.

The Influence of Digital Retail Environment on Consumer Purchasing Behavior: A Causal Study

As e-commerce continues to evolve, understanding consumer behavior in the context of online shopping becomes increasingly challenging. This study investigates the impact of purchasing attitudes among Saudi customers within the online clothing environment. By collecting 410 responses from residents of Riyadh, Saudi Arabia, the study emphasizes the convenience aspect of online and virtual markets and employs advanced statistical techniques, specifically SPSS-AMOS software, including confirmatory factor analysis, path analysis, and structural equation modeling. The findings reveal several key insights: perceived entertainment, perceived ease of use, and perceived usefulness significantly and positively influence the user experience on websites. The research highlights the importance of website quality indicators, such as perceived entertainment, ease of use, and usefulness, in shaping the user experience within the online clothing environment. It confirms that website quality, encompassing indicators of the user experience, exhibits a significant positive association with online impulse buying behavior. Additionally, the flow experience, which refers to the immersive and enjoyable state when browsing a website, also demonstrates a statistically significant and positive effect on online impulse buying behavior. These findings offer valuable insights for businesses and marketers seeking to understand and adapt to the evolving landscape of e-commerce, specifically concerning online clothing purchases.

Sensory marketing: the mediating role of hedonic emotions between multisensory experiences and mall patronage intention

PurposeProviding positive and memorable shopping experiences has become essential for retailers. As the retail industry strives to create multisensory experiences for consumers, it is equally important to understand the emotions and pleasure such experiences evoke. The current study aims to investigate how multisensory experiences induce hedonic emotions in retail shoppers. It explores the mediating role of hedonic emotions in between multisensory experiences and shopping mall patronage intention.Design/methodology/approachThe study is descriptive; the data was collected using the mall intercept survey method. A total of 380 shoppers participated in and responded to the survey administered at the mall. The collected responses are analyzed using partial least squares structural equation modeling.FindingsOur findings support the idea that hedonic emotions play a significant role in the retail environment by influencing retail patronage intentions. Also, the multisensory experiences have a positive effect on patronage intention as well as the hedonic emotions of shoppers.Research limitations/implicationsThe present study provides theoretical and managerial implications for academicians and retail marketing.Originality/valueThe present research contributes to the existing literature by introducing the concept of multisensory experiences in the retail context and its impact on hedonic emotions and adding to the concept of inference theory.

Digital Transformation in Retail: Strategies for Brick-and-Mortar Stores

Digital transformation has become imperative for brick-and-mortar retail stores facing the challenge of adapting to evolving consumer behaviors and competitive pressures in the digital age. This paper explores strategies and best practices for leveraging digital technologies to enhance customer experience, optimize operations, and drive growth in traditional retail environments. The rapid adoption of online shopping, mobile commerce, and digital platforms has reshaped consumer expectations and shopping habits. Brick-and-mortar retailers must embrace digital transformation initiatives to remain relevant and competitive in a dynamic retail landscape. This study examines successful case studies and empirical research to identify effective strategies for integrating digital technologies into retail operations.

CUSTOMER SEGMENTATION USING RFM ANALYSIS

This research presents a comprehensive approach to customer segmentation using Recency, Frequency, and Monetary (RFM) analysis, combining statistical insights, data visualization, and machine learning techniques. The study utilizes a real-world dataset obtained from a retail environment, aiming to categorize customers based on their recent purchasing behavior, visit frequency, and monetary contributions to the store. The code begins with data preparation and exploration, ensuring data integrity by addressing issues such as negative quantities and missing customer identifiers. Following this, the Recency, Frequency, and Monetary metrics are computed, providing a holistic view of customer engagement and spending patterns. Visualizations, including violin plots, histograms, and box plots, are employed to intuitively convey the distribution of these metrics. The research then delves into the quantile-based segmentation of customers, allowing for a more granular classification. Quantiles are calculated to divide customers into four segments for each RFM metric. The resulting quantile labels are applied to the dataset, enabling the creation of a compound RFM quantile that combines recency, frequency, and monetary information. This combined quantile facilitates the definition of distinct customer segments. To further enhance the interpretability of customer segments, the study introduces a set of rules for labeling customers based on their RFM quantiles. These rules yield segments such as "Best Customer," "Loyal Customer," "Big Spender," "Dead Beats," and "Lost Customer." The resulting customer segmentation is presented visually through histograms and a pie chart, providing a clear and concise representation of the distribution of customers across different segments. Moreover, the research integrates machine learning models, including XGBClassifier, and CatBoostClassifier, to explore the potential of automating the segmentation process and predicting customer segments based on historical data. However, the machine learning aspect is introduced with commented-out sections, leaving room for further exploration and experimentation. In conclusion, this research contributes a comprehensive and detailed code implementation for RFM-based customer segmentation. The integration of visualization techniques aids in the interpretation of customer behavior, while the inclusion of machine learning models opens avenues for predictive analytics in customer segmentation. The presented approach provides valuable insights for businesses seeking to tailor marketing and customer relationship strategies based on individualized customer segments. KEYWORDS— Customer Segmentation, Frequency, Monetary Value, Recency, RFM Analysis.

Consumer behavior in immersive virtual reality retail environments: A systematic literature review using the stimuli‐organisms‐responses (S‐O‐r) model

AbstractWith the rising popularity of immersive virtual reality (iVR) technologies, retailers are increasingly seeking innovative ways to create unique digital shopping experiences for their consumers. However, existing literature lacks a unified and comprehensive review that examines the interplay between virtual stimuli and consumer behavior in iVR shopping environments. To fill this gap, we conducted a systematic literature review, employing the Stimulus‐Organisms‐Responses (S‐O‐R) model as the underlying theoretical framework. This review analyzed empirical research on consumer behavior in iVR retail environments by focusing on experimental studies. Following the thematic analysis, we categorized the outcomes into descriptive themes to better comprehend consumer behavior within each theme. Our findings provide valuable insights for retailers and marketers aiming to enhance the consumer shopping experience using iVR technologies and suggest directions for future research.

Commercial techniques to improve customer service

The advance of digital platforms has transformed the shopping process, making it more accessible and practical. In this study, we seek to understand the preferences of customers of commercial premises of Malecón 2000 in the city of Guayaquil, both in their face-to-face and online shopping. The sample focused on customers between 20 and 40 years old, using a descriptive research with a quantitative approach through surveys in Google Forms. The studies surveyed highlight different aspects of customer service and commercial techniques, while the results obtained underline the importance of direct interaction with merchants. They also highlight the need to improve product diversity and the online shopping experience to maintain market relevance in an increasingly competitive retail environment.

Associations Between the Food Retail Environment and Healthy Food Availability Among Urban Versus Rural Maryland Corner and Convenience Stores

Associations Between the Food Retail Environment and Healthy Food Availability Among Urban Versus Rural Maryland Corner and Convenience Stores