Real Store Research Articles

A COMPARATIVE STUDY ON ONLINE AND OFFLINE SHOPPING

This study aims to identify the factors that influence customers' choices between in-store and online shopping, as well as any relationships (direct or indirect) between these factors and the two channels. To better comprehend the factors that impact our choices to purchase online or in a real store, this research will function as a theoretical examination. Drawing findings from graphical analysis requires first determining which demographic groupings prefer online shopping over more conventional brick-and-mortar establishments. An analysis of correlation can shed light on the nature of the connection between the product's price and the quantity sought for. Simple regression analysis is a statistical method that uses the value of one related variable to estimate the value of another connected variable. Here, we'll estimate the quantity purchased online using the cost value. Clothing and cosmetics account for the bulk of women's monthly online product purchases, with an average of one unit per customer. The most effective and widely seen form of advertising is discount commercials targeted at female consumers. The average male spends more money each month than the average female, shops at supermarkets instead of specialty businesses, and prefers to purchase gaming gear online. The quantity bought has an inverse relationship with the cost per unit. Keyword; Consumer, online shopping, offline shopping, consumer behavior, regression analysis, graphical analysis, correlation analysis, online, offline, products, shopping .

Using postural data and recurrent learning to monitor shoplifting activities in megastores

SummaryRecently, researchers have placed a great deal of emphasis on modeling activity patterns to better understand human behavior. Several approaches have been researched so far to develop automatic human activity recognition systems that infer detailed semantics from visual images, aiming to understand real human behavior patterns. However, there is still a need for a cost effective solution to distinguish human actions in the real‐world environment. With this encouragement, a novel approach is proposed to recognize shoplifting acts by examining the posture evidence of the human being. This approach begins by obtaining the two‐dimensional pose reflecting human's body joints as a skeleton from the recorded frames. Subsequently, a preprocessing step is used to preprocess skeleton data, which can handle the occlusion too. Postural feature generation is then used to extract pertinent features from such preprocessed skeletons. Finally, feature deduction is performed to downsize the derived features to a smaller dimension, and activity classification is performed on such reduced features to identify shoplifting behaviors in real time. A synthetic shoplifting dataset and real store recorded videos are used to conduct the experiments, the findings of which appear more promising than those obtained using other cutting‐edge methods, with an accuracy of 97.36% and 91.66% for synthesized and real store recorded inputs.

Application and testing of RFID Software-Based Shielding in real fashion retail stores

PURPOSE: The present paper investigates the real performances of Software-Based Shielding (SBS) in two different stores of fashion retailers located in Northern Italy. DESIGN/METHODOLOGY/APPROACH: The study is based on a double case study analysis. Six different factors have been chosen, with two levels each. Namely, we investigated two different (i) stores; (ii) reader models; (iii) power levels; (iv) classification methods; (v) training data sets and (vi) settings of reference tags. The results have been evaluated in terms of overall and specific accuracies, and in percentage of false front (i.e., tags wrongly located in the sales floor area). FINDINGS: SBS proves to be a sound method for classifying tags’ location during normal operations in real-life stores, with overall accuracy up to 0.95. Of the two readers, reader A shows better results in terms of both overall and front accuracy, whereas reader B performs better in terms of rear accuracy and percentage of false front. With respect to the classification method, the combination of Neural Network with reads from reader A provides the best results. With respect to the training data, the use of front and back reads for training performs mostly better than the training with sole front data. ORIGINALITY: We are not aware of any other study that performed and reported results of SBS testing under normal operations in real stores. To the best of our knowledge, this study is the first one to report such results. RESEARCH LIMITATIONS: Main limitations of our research are the limited set of factors and levels, and the specific Logistic Regression and Neural Network methods that we used. Also, we did not consider tags disposition and density in our study. PRACTICAL IMPLICATIONS: We prove that SBS is a feasible option that could replace physical shielding in retail stores. We call to action for further research on this topic, and for retailers to test it in different store locations.

Glass Virtual Try-On

Abstract: Virtual try-on technology allows people to explore the look of accessories, makeup, hair extensions, hair color, clothing and much more for themselves. Virtual try-on offers many advantages over real attempts, speeding up the process gives you the opportunity to test hundreds of products without the need to access a real store. The test process is performed on a reconstructed 3D face from a embedded image that allows the user to see the visible face and mirrors with different views. The process is fully automatic and does not require the user to provide anything other than the image and the name of the glass frames for testing.

<em>Roblox</em> and Meta Verch

<em>Roblox</em> and Meta Verch

Priming shoppers’ well-being goal in grocery stores: Moving toward healthier food choices?

At the times of obesity epidemic, innovative ways to nudge food shoppers toward healthier choices are needed. Key ideas from the conceptual metaphor processing, food symbolism and contextual priming literatures are synthetized to argue for the idea that visual, olfactory and gustatory cues can activate shoppers’ well-being goal and guide their in-store movements and healthy food purchasing behaviors. Two field experiments, separated by an 8-month interval, are conducted in the same grocery store. The results show that priming the well-being goal in real store can push consumers to move toward spots where healthier options are available – materializing also into greater sales of yogurts, vegetables and heart healthy-labeled products. Counterintuitively, the well-being goal activation possibly first facilitate approaching indulgent foods. Yet, the actual sales of palatable foods such as ice cream and minced beef meat may in fact diminish. This research spurs numerable academic and practical implications.

РІТЕЙЛ 5.0: ОПТИМІЗАЦІЯ СПОЖИВЧОЦЕНТРИЧНОГО ПІДХОДУ В ЦИФРОВОМУ СЕРЕДОВИЩІ

The article is devoted to the definition and disclosure of the essence of the concept of Retail 5.0 trade. The process of the evolution of trade from the point of view of consumer needs orientation approaches has been studied. It is established that in the Retail 5.0 trade concept, the consumer is in the center of attention, which makes Retail 5.0 a consumer-centric trade concept. It is concluded that customer-centricity is absolute in Retail 5.0 in a digital environment that uses a mixed trade format, which combines in one ecosystem digital platforms and real stores or points of sale, delivery systems, forming the Retail 5.0 ecosystem

Consumer behaviour and experiences in a naturalistic online grocery store: implications for nutrition research.

Naturalistic online grocery stores could provide a novel setting for evaluating nutrition interventions. In 2021-2022, we recruited US adults (n 144, 59% low-income) to complete two weekly study visits: one in a naturalistic ('mock') online grocery store developed for research and one in a real online grocery store. Participants selected groceries and responded to survey questions. Analyses examined survey responses and expenditures on fifteen food categories (e.g., bread, sugar-sweetened beverages). Nearly all enrolled participants completed both visits (98% retention). Moreover, nearly participants all reported that their selections in the naturalistic store were similar to their usual purchases (95%) and that the naturalistic store felt like a real store (92%). Participants' spending on food categories in the naturalistic store were moderately-to-strongly correlated with their spending in the real store (range of correlation coefficients: 0⋅36-0⋅67, all P-values < 0⋅001). Naturalistic online grocery stores may offer a promising platform for conducting nutrition research.

A Metric for Assessing, Comparing, and Predicting the Performance of Autonomous RFID-Based Inventory Robots for Retail

RFID technology is being widely adopted by retailers due to its accuracy, versatility and reduction of operational costs. Most commonly, RFID in retail is used for taking frequent and accurate inventories of items in the stores. Usually, RFID inventories use handheld RFID devices, which makes the task tedious, costly, and prone to human errors. More reliable, fully automatic alternatives exist, such as smart shelves, overhead RFID antennas, and RFID equipped robots. Among them, robots seem to be the preferred choice by retailers with large stores. However, retailers need an objective way to compare the different options for inventory solutions and to calculate the return on investment (ROI) of each of them before they make and investment decision. In this article we present a metric for assessing, comparing, and predicting the performance of autonomous RFIDbased robots in retail stores. The metric models both the store and the robot, and predicts the performance of a given robot when inventorying a specific store. The metric also allows to compare the performance of different RFID robots in different stores. The metric has been developed using experimental data, and has been validated in a real store.

The effect of addition Ag and MnO2 nanoparticles in the hydrogen storage of ethyl 2-((5-methoxybenzo[d]thiazol-2-yl)thio)acetate (organic: Inorganic nanohybrids)

This research included the synthesis of ethyl2-(benzo[d]thiazol-2-ylthio)acetate (EBTA) by reacting 2-mercaptobenzothiazole with ethylchloroacetate in the presence of potassium hydroxide. The compound was characterized using 1HNMR and FTIR. This compound was used to prepare two of its organic: inorganic nanohybrids with nano-manganese oxide (EBTA-MnO2) and with nano-silver (EBTA-Ag). The resulting composites were characterized using FTIR, XRD, SEM, EDX and TEM. The measurements proved that the reaction occurred successfully through the one-step reaction. These compounds were used in the application of hydrogen storage, and the study proved that the addition of these nanomaterials gave a great ability to increase hydrogen storage. The results showed that the compounds (EBTA), (EBTA-Ag) and (EBTA-MnO2) gave 0.99, 3.63 and 4.05 wt% hydrogen storage capacity, respectively. Also the study showed that the nano-hybrid (EBTA-MnO2) gave more storage efficiency than (EBTA-Ag), because manganese oxide contains two oxygen atoms, which act as effective real stores to increase the capacity hydrogen storage.

Is Platinum a Real Store of Wealth?

The research goal is to determine whether platinum can be seen as a good investment. For this purpose, content analysis of documents and deep learning neural networks with recurrent neural network were used. The results show that it pays for a koruna investor (a person holding their wealth in Czech koruna) to preserve their wealth physically in the form of a precious metal—specifically, platinum. The research confirms that platinum is a store of value but also a koruna investor’s wealth multiplier. This can be due to its rare occurrence in nature, but also to its unique use in manufacturing. A research limitation is the period for which the data were used. The finding that platinum is a store of value, as well as a wealth multiplier, can thus be concretized when using the data for a five-year period. It shall also be added that no turbulent changes are anticipated (such as interruption of platinum supply, unexpected government regulation of trade, etc.).

Colours and price offers: How different price communications can affect sales and customers’ perceptions

It has been studied that colours are important pieces of information in everyday life and that they ‘boost memory, engage participation, attract attention, convey messages, and create feeling’. Despite the awareness of the importance of colours also for marketers, academic research is not abundant and there is a lack of studies that link colours to the management of the marketing mix. The present work tries to understand how colours may affect price perceptions and how the effectiveness of different price mechanisms may vary using different colours in the FMCG market.A 2x2 (red vs yellow special display/discount vs LPG price deal) experiment has been conducted in a real store environment thanks to the collaboration of a leading italian chain.The results obtained from a three-way analysis (instore observations, instore questionnaires and sales data) can add valuable pieces of information regarding the effectinevess of colours in improving the performance of instore marketing strategies.

CONSUMER BEHAVIOR TOWARDSE- COMMERCE: ONLINE SHOPPING

A good example of a business revolution is online purchasing. Individuals and groups can now live simpler and more imaginative lives thanks to ecommerce. Consumer behaviour in online purchasing differs from that in a real store where he or she can see the merchandise. Traditional or physical stores are rapidly being replaced by websites. Customers' trust has grown over time. The need for internet shopping platforms has skyrocketed. The number of these has risen. On the one hand, websites have fueled fierce rivalry, resulting in better and cheaper items for consumers. Customers, on the other hand, have privacy concerns when it comes to their data. to internet shopping The way people shop for and purchase goods and services is changing as a result of the internet. It has quickly grown into a worldwide sensation.This research paper attempts to analyze the consumer behavior towards online shopping, and the various factors influencing trend of online shopping. Keywords: online shopping, consumer behavior, physical market, internet

Trend Hunters E-Shop for Trending Fashion

The main goal of the study is to learn the importance of e-shop in today's competitive market. How will offline retailers survive? And how to provide best services?How to present better product in less prize and maintain relationship among the existing customers. In today’s time it is very advantageous to provide your services and product online along with the offline services it will add excellence to a business, because a lot of people prefer shopping online and Online shopping is a common trend among the customers. However, with the advent of the Internet, the condition of the shopkeepers has become miserable. In addition, a new trend of online shopping has emerged in the last years, which offers a lot of possibilities for buying items and products. People are getting used to this trend; however, some people still go to the store to make purchases. The study of this topic will help in to understand the effect of online stores and it will also help in developing and understanding of the different frameworks and models related to E-shop and the advantage of developing an E-shop for a real store, outlets. Now days due to changing business environment it is very important to respond the need of customers in most effective manner. If you’re existing customers want to view your shop online to have easy and quick access to your products and services.

Numerical Comparative Study on the Effective Replacement Thickness of Traditional Stone Coarse Aggregate or Steel-Slag Aggregate Mixtures in Improved Soft Fine Soils

This study uses Steel Slag Coarse Aggregate (SSCA) as a mixture replacement, preamble material to improve soft soils, which is economic, and has good effect environment. Recently, the development and utilization of by-product, waste and recycle materials must be studied and investigated as a source of improved material for soft soils as, an economic and good effect environmental. The study analyzes effects of both replaced mixtures, (SSCA) or (TSCA) on improved soil bearing capacity and expected settlement after verifying the model. Numerical modeling of the one of real store loaded strip using, PLAXIS, 2D, strain deformation behavior to achieve field visible and measured deformations of untreated soft soil. Numerical studies were devolved to investigate geomechanics parameters improved to compare between using (SSCA) or (TSCA) as, replacement mixture. Results demonstrate that using (SSCA) improved compressibility and strength of shallow soft soil layer significantly than using (TCSA) mixture, while (SSCA) improved strip footing ultimate bearing capacity, (UBC), by 84.4% compared with increase of 20.5% when using (TCSA) mixture at the same thickness. In addition, the study highlights the effective (SSCA) replacement thickness ranges between (0.65 ~ 0.80) footing width.

“Fronts for Drugs, Money Laundering, and Other Stuff”: Convenience Stores in the Retail Food Environment

ABSTRACT There have been calls for more research to investigate the sociocultural context of retail food environments. This paper examines how a segment of Ottawa, Ontario, Canada, residents described convenience stores (CS) in their local retail food environments. 84 social media discussions from Ottawa residents pertaining to their local retail food outlets were qualitatively analyzed, and three themes were formulated: 1) CS are interchangeable, 2) CS are not ‘real stores,’ and 3) CS are dangerous retail food outlets. We argue that these social constructions of CS have implications for healthy food environments and offer suggestions for future research.

Using a Naturalistic Store Laboratory for Clinical Trials of Point-of-Sale Nutrition Policies and Interventions: A Feasibility and Validation Study.

Point-of-sale policies such as warnings and taxes are promising tools for improving the nutritional quality of food purchases. Research studies conducted in naturalistic store laboratories could improve the quality of evidence about point-of-sale interventions by allowing for realistic exposure in a controlled setting. This study aimed to assess whether purchasing behavior in a naturalistic store laboratory setting was similar to real-life purchasing behavior and to evaluate participants’ perceptions of store realism and the acceptability of research study protocols in this setting. In a longitudinal observational study in 2019, Latinx parents in North Carolina (n = 61) attended five weekly visits at the UNC Mini Mart, a naturalistic store laboratory that resembled a small convenience store. At each visit, participants purchased a week’s supply of beverages. Purchases of beverages in the Mini Mart were compared to participants’ purchases from receipts submitted the week prior to the study. Analyses compared the percentage of participants buying sugary drinks and non-sugary drinks in the Mini Mart vs. in real stores using Chi-Square tests with Fisher’s p. The percentage of parents who purchased sugary drinks in the Mini Mart (93%) was not significantly different from the percentage who purchased sugary drinks during the week before the study (74%, p = 0.28). The percentage purchasing non-sugary drinks was similar in the two settings (85% in the Mini Mart vs. 85% from receipts, p = 0.33). Nearly all participants reported that their Mini Mart purchases were similar to real-life purchases (96%); the Mini Mart felt like a real store (94%); they could find all the beverages they were looking for (92%); and they could imagine doing their real-life beverage shopping in the Mini Mart (92%). Moreover, retention was high, with 97% of participants attending the final study visit. These results indicate that naturalistic store laboratories are a promising method for increasing the ecological validity of trials to evaluate point-of-sale interventions.

MyCart : An Online Shopping Platform

Online shopping has obtained very important position in the 21st century as most of the people are busy, loaded with hectic schedule. In such a situation online shopping became the easiest and most suitable mode for their shopping. This paper describes the development of an e-commerce Web site based on a virtual world that replicates a real store in order to offer a more familiar interface to the user, but overcoming the problems of reality offering a customized presentation of items to each consumer. The technology used is Java. The system architecture is based on a client/server model, where the server manages the description of the items.

Can a retail environment be simulated by photographs?

ABSTRACT Photographs are commonly used in store atmospherics research, although their ecological validity lacks conclusive support. To this end, we examine the effect of different representation media of a retail environment (i.e. one photograph, three photographs, or a real store visit) on customer experience, satisfaction, and behavioural and attitudinal loyalty. Two studies examine the robustness of our findings across low- and high-experience stores. The results show that only in the high-experience store environment, a real store visit results in a significantly higher average perceived customer experience. Moreover, the chosen representation medium affects satisfaction and behavioural loyalty in both store types. Again, a real store visit results in higher scores. Upon studying low-experience stores and/or focusing on attitudinal loyalty as the outcome variable, pictures, however, do seem to be ecologically valid. To conclude, whether it is safe to simulate a retail environment with photographs depends on the particular retail context and the outcome variables under study.

LSTM Based Sales Prediction System for Supermarket

Many supermarkets today do not have a better forecasting system for yearly sales. This is due to the lack of skills, resources, and knowledge to make sales estimations. The use of the conventional statistical technique to forecast grocery supermarket sales has left many demanding situations unaddressed and, in general, results in the creation of predictive models that perform poorly. The era of big data, coupled with access to massive computing power, has made deep learning a go-to for sales forecast. This proposed system investigates forecasting sales for several stores. The essential variables that helped in better sales forecast were store type, date, item and sales. Product sales forecasting is a significant aspect that mainly aims to manage the purchase. Forecasts are crucial, especially in determining the accuracy of estimating the future demand for goods and inventory stock levels, which has been vital, mainly in the Grocery or supermarkets. Consider if goods are not available readily or the availability of goods is more than the demand, it can compromise overall profit. As a result, product sales forecasting may be critical to ensure that losses are reduced. Besides, the issue is becoming complicated for retailers to add specific consumer criteria that involve new, ever-changing seasonal preferences and volatile product marketing items. Hence a forecasting model is developed using Long short term memory (LSTM) to improve product sales accurate forecasts. The proposed model is mainly targeted to support the future purchase and a more precise prediction of sales and is not meant to alter Forecasting's existing subjective methods. A model based on a real grocery store's data for four years is developed to predict the store's sales. This method's impact is to forecast the availability of products in stores to ensure that they have just enough products at the right time.