Retail Stores Research Articles

Financial Performance among Selected Liquified Petroleum Gas (LPG) Retail Stores in Talisay City, Cebu

The Liquified Petroleum Gas (LPG) sector plays a noteworthy part in the local economy, supplying essential energy resources for residential and commercial use. The COVID-19 pandemic has brought massive distractions that significantly affect the financial performance of companies, regardless of the sector they belong to, and this sector is not exempted. This study examined the financial performance of these LPG retail stores in Talisay City, Cebu, to know if they recovered financially, particularly in recent economic downturns and market forces. After examining the financial data for the years 2022 and 2023 using the identified financial ratios, the authors found that all participating LPG retail stores showed a positive financial performance in terms of their net profit margin, current ratio, debt-to-equity, asset turnover, and cash flow to debt ratios. This implies that LPG retail stores operate efficiently, maintain robust profitability, manage financial obligations correctly, and ensure sufficient liquidity. Additionally, it can give owners a positive perspective on the growth and stability in Talisay City, Cebu.

Breaking into the black box of customer perception towards robot service: Empirical evidence from service sector

The advent of artificial intelligence and machine learning has enabled robots to serve in consumer market for a better customer experience. Nevertheless, acceptance of robotic technology among consumers is still lacking. Therefore, this study has developed an integrated model with robot appearance, expectation confirmation model, diffusion of innovation and theory of planned behavior and empirically investigates customer intention to use service robot. The research model is empirically tested with 349 responses retrieved from customers visiting retail stores. Statistical results have revealed that customer innovativeness, compatibility, behavioral control, expectation confirmation, service robot appearance and subjective norms explained R2 80.1 % variance in customer attitude to use service robot. Practically, this research has suggested that policy makers should pay attention in innovativeness, compatibility, perceived behavioral control, expectation confirmation, robot appearance and subjective norms to boost robot service acceptance among customers. This study is original as it develops an integrated model with the combination robot appearance, theory of planned behavior, expectation confirmation and diffusion of innovation theory. In addition to that customer self-identity is conceptualized as moderating factor and hence distinguishing current research with past studies.

Modelling the recovery time from peak loads in a full-scale horizontal flow wetland in Sicily

The aim of this study was to simulate the water flow and reactive transport of pollutants in a horizontal flow (HF) wetland to better understand the recovery time of the treatment performance for peak load events. For the simulation, the processes-based model HYDRUS and its Wetland Module is used. The system under investigation is the first stage of the 9-years old hybrid treatment wetland of a large retail store, located in Catania, Italy. For the calibration of the hydraulic model, the data of a tracer test was used. The data set of the systems is available for a seven year period including organic matter and ammonia nitrogen. The data was split into a standard event representing low loading conditions and determined peak load events with high loadings. The results show that the response time of the model correlates with the hydraulic retention time from the tracer experiment and indicates that higher peak load concentrations at the inlet of the system lead to a longer recovery time of the wetland.

ПОЛУЧЕНИЕ КОРМОВОГО СМУЗИ ИЗ ОТХОДОВ ОВОЩЕЙ И ФРУКТОВ

Background. Currently, about 50-60% of vegetable and fruit waste is generated at fruit and vegetable storage facilities, retail stores, distribution centers of retail chains from the total volume of discarded products. One of the solutions to reduce waste is to propose a way of their processing: fodder smoothie production. Purpose. To select technological processing modes for obtaining a sample mixture of fodder smoothie from vegetables and fruits. Materials and methods. For obtaining a model mixture of fodder smoothie 30% of tomatoes, 10% of potatoes and 20% each of carrots, cabbage, apples were used. To work out the technological parameters of obtaining the sample mixture, the following were recorded: grinding time, grinding speed, appearance of the obtained model mixture, as well as pH and mass fraction of soluble solids were determined.Results. The pH of the sample mixture of fodder smoothie was 6.4, the value of the mass fraction of soluble solids ranged from 14.2% to 16% depending on the parameters of producing the mixture. The sample mixture was mushy of brown color. Conclusion. The technological parameters were selected for the investigated sample mixture. The pH of the crushed product does not change with the change of technological parameters. Mass fraction of soluble solids increases with increasing the amount of product grinding time and the grinding speed.

The influence of CSR, social media marketing and store environment on customer purchase intention of cosmetic products

Today's world of intense competition and shifting business practices has led to a huge increase in both client demand and retailer power. For producers to survive and prosper, a long-lasting relationship with consumers is essential. The cosmetics industry in China has experienced remarkable growth in recent years. After the US, the nation ranked as the second-largest cosmetics market globally in 2020. Therefore, the goal of this study is to look into the variables that influence Chinese customers' intentions to purchase cosmetics products in relation to CSR, social media marketing and store environment. Primary data was collected using questionnaires from 220 consumers from multiple cosmetics department stores located in Otto Retail Store in Chengdu, China. The findings derived from the Pearson Correlation Coefficients demonstrate a statistically significant positive association between three variables: CSR, social media marketing and store environment on customer’s purchase intention of cosmetic products at Otto Retail Store, Chengdu, China. The results demonstrate a statistically significant and positive relationship between all three factors on customer’s purchase intention of cosmetic products and are highly significant at 1% level. Store environment has the highest correlation with customer’s purchase intention of cosmetic products (r=0.610, p<0.01), followed by social media marketing (r=0.567, p<0.01) and CSR (r=0.532, p<0.01). Results of regression analysis have been used to test all the hypothesis to ascertain the extent of relationship with the variables that measures factors affecting customer’s purchase intention. All the three independent variables showed significant positive relationship with customer’s purchase intention with p<0.005.

Technology in fashion retail: exploring the nexus of in-store technology, customer experience, and store image

ABSTRACT This research aims to shed light on the complex interplay between in-store retail technologies, shopping experience, and store image in the context of fashion retail outlets. The SOR (Stimulus-Organism-Response) based Bitner’s model has been selected as the theoretical foundation of the present study. A total number of 245 customers from retail fashion outlets of Jammu & Kashmir and Delhi regions of India were sampled using convenience sampling. The hypotheses were tested using the technique of Structural Equation Modelling. Findings indicate that in-store retail technology positively influences customers’ experience (cognitive, affective, social, relative advantage component), which in turn positively impacts store image. The construct ‘customer experience’ was found to significantly mediate the relationship between ‘in-store technology’ and ‘store image’. Using Bitner’s model as theoretical foundation, the findings of the study provide useful insight that in-store technology is a crucial determinant for building a better store image through enhanced customer experience, which could be seen as a significant contribution to the extant literature.

Benarkah Suasana Toko dapat Mempengaruhi Pembelian Impulsif di MINISO Trans Studio Mall Bandung?

Abstracts This study aims to evaluate the influence of store atmosphere on customers' impulse buying behaviour, specifically at MINISO at Trans Studio Mall Bandung. MINISO is a specialized retail store that offers a wide range of household and consumer goods, such as cosmetics, stationary, toys, and kitchenware. The study examines the impact of cleanliness, lighting and colour, and display or layout on cognitive behaviour. It involves a sample of 100 participants who visited MINISO, including both residents of Bandung and individuals from outside places. Correlation study indicates that cleanliness did not have a significant impact on cognitive behaviour. However, there were strong links observed between lighting and colour, as well as presentation or layout. The findings emphasize the significance of establishing an enjoyable retail environment to enhance customer happiness, yet these do not have a significant impact on stimulating impulsive purchasing behaviour.

Two years of data monitoring of all-CO2 retail stores within the MultiPACK project

This paper presents the results of a 24-month field monitoring of CO2 transcritical units designed to satisfy all the thermal needs of food retail stores, namely refrigeration, heating and cooling. The units, adopting state-of the art technologies, such as two phase ejectors and parallel compression, are developed within the H2020 project MultiPACK. The monitored supermarkets are located in Italy, in two different climatic areas, featuring different heating and cooling demands for indoor comfort, as well as diverse building type and display cabinets mix. Long lasting measurements allow for evaluation of energy and efficiency related KPIs, together with operational indicators. These figures are relevant for benchmarking with traditional solutions.

Global invasion and biosecurity risk from the online trade in ornamental crayfish.

Trade in undomesticated ornamental animals has rapidly expanded beyond brick-and-mortar retail stores to now include growing numbers of internet marketplaces. The growing volume, diversity, and origins of invasive non-native species in trade challenge already weak national biosecurity policies. Despite widespread focus on vertebrates, many knowledge gaps exist regarding the online global trade of ornamental invertebrates. We conducted the first global assessment of the online trade in and associated invasion risk of freshwater crayfishes, which are increasingly popular aquarium animals. We systematically examined e-commerce marketplaces in multiple languages, scrapping information that included species identity, price, quantity, and shipping designation from each crayfish listing. Next, we combined geographic pathways of shipping associated with online trade (introduction risk) and environmental suitability modeling (establishment risk) to estimate global risk of non-native crayfish invasion risk. We identified hundreds of online marketplaces and thousands of sale listings in 33 countries (5 continents) involving 60 species and representing a selling value of ∼US$1.5 million. Invasion risk of non-native crayfish in trade was widespread, with geographic hotspots coinciding with both elevated opportunities for introduction (greater shipping offerings) and establishment. Precise characterization of the online species trade is fundamental to support new and reformed biosecurity policies, build industry partnerships, and design educational campaigns to prevent species invasions through trade. We found that the taxonomy, geography, and economics of the global online ornamental crayfish trade are vast and require greater attention.

Demographic Characteristics: Predictors of Theconsumers Buying Behaviour in Organized Retail Stores

Demographic Characteristics: Predictors of Theconsumers Buying Behaviour in Organized Retail Stores

Anchoring decisions: the role of decoy pricing in consumer choices

PurposeHospitality firms aim to increase their profits by implementing a variety of marketing activities, including using decoy pricing to provide alternative choices for consumers. Decoys are relatively higher-priced offerings that signal lower value than the other offerings in the consideration set. The purpose of this research is to investigate the influence of decoy pricing on consumer choices across various contexts in the foodservice and hotel industries.Design/methodology/approachAcross the pilot and four main studies, the current research employs a sequential exploratory mixed-method design to investigate the influence of decoy pricing in the foodservice and lodging industries. The qualitative part of this research was based on two focus groups, followed by a pilot study and four main study experiments.FindingsThe results show that decoy pricing escalates consumers’ choices of more expensive product bundles in both restaurant and hotel cancellation policy contexts. However, decoy pricing does not increase the selection of more expensive hotel product bundles.Originality/valueWhile decoy pricing has been utilized as an effective revenue maximization strategy for product placement in retail stores, less is known about how promotional advertisements with decoy offers influence hotel and restaurant customers to choose more costly options. Specifically, this is the first study that explores whether decoy pricing and product/service bundling can encourage customers to select more expensive offers in hotel and restaurant contexts, considering the types of hospitality bundles that may limit this effect.

Multi-Omics Profiles of Small Intestine Organoids in Reaction to Breast Milk and Different Infant Formula Preparations.

Ensuring optimal infant nutrition is crucial for the health and development of children. Many infants aged 0-6 months are fed with infant formula rather than breast milk. Research on cancer cell lines and animal models is limited to examining the nutrition effects of formula and breast milk, as it does not comprehensively consider absorption, metabolism, and the health and social determinants of the infant and its physiology. Our study utilized small intestine organoids induced from human embryo stem cell (ESC) to compare the nutritional effects of breast milk from five donors during their postpartum lactation period of 1-6 months and three types of Stage 1 infant formulae from regular retail stores. Using transcriptomics and untargeted metabolomics approaches, we focused on the differences such as cell growth and development, cell junctions, and extracellular matrix. We also analyzed the roles of pathways including AMPK, Hippo, and Wnt, and identified key genes such as ALPI, SMAD3, TJP1, and WWTR1 for small intestine development. Through observational and in-vitro analysis, our study demonstrates ESC-derived organoids might be a promising model for exploring nutritional effects and underlying mechanisms.

Building the Lands’ End digital asset management content hub

Founded in 1963, Lands’ End is a digital retailer of clothing and home products available through online marketplaces and retail stores. In 2019, the company transitioned to a new enterprise digital asset management solution for its in-progress and final assets. This paper summarises how the new system has expanded into a content hub for a wide variety of digital assets, including images, video, catalogue pages, e-mails and integrations with enterprise systems, and describes the challenges, benefits and opportunities.

A web-based travel package management system integrated with QR code

The tourism industry is associated with people travelling either domestically or abroad, for business, social, or recreational reasons. This industry integrates numerous services and activities such as tourism organization, marketing, hotel industry, transportation services, food and beverage activities, retail stores and various other activities under one umbrella. In addition to generating income and jobs, tourism is the best way to promote the nation's image. As the economy and living conditions have improved, so too has the tourist sector, and more people are turning to vacations as a way to alleviate stress and unwind. Currently, travel agencies handle a lot of data with low efficiency and a lot of mistakes. Therefore, this study developed a comprehensive integration of QR code for package travel management system that caters to users in Malaysia, offering functionalities such as itinerary customization, QR code generation and access to essential travel information. The development of this project adopts the Waterfall Methodology, encompassing phases such as planning, requirement analysis, design, implementation and testing. The application is crafted using the Visual Studio Code. The study conducted a User Acceptance Testing (UAT) using questionnaires to evaluate the system's effectiveness and user-friendliness to thirty respondents including family members of frequent travellers and randomly selected community members. Positive feedbacks with Perceived Ease of Use (PEU) scoring 3.6, Attitude of Using (ATT) at 3.7, Perceived Usefulness (PU) scoring 3.4, and Intention to Use (IU) obtaining 3.9, were gathered from the analysis and findings that emphasizing the QR code system's potential as a cost-effective and efficient solution for travellers to monitor and optimize their travel experiences. Future work involves adding maps for easy navigation and implementing augmented reality (AR) for virtual destination previews.

Generating in-store customer journeys from scratch with GPT architectures

We propose a method that can generate customer trajectories and purchasing behaviors in retail stores simultaneously using Transformer-based deep learning structure. Utilizing customer trajectory data, layout diagrams, and retail scanner data obtained from a retail store, we trained a GPT-2 architecture from scratch to generate indoor trajectories and purchase actions. Additionally, we explored the effectiveness of fine-tuning the pre-trained model with data from another store. Results demonstrate that our method reproduces in-store trajectories and purchase behaviors more accurately than LSTM and SVM models, with fine-tuning significantly reducing the required training data.Graphic abstract

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.

Nutrient Analysis of Raw and Cooked USDA Prime Beef Cuts.

Nutrient composition data that accurately represent available beef products are critical to understanding beef's role in healthy dietary patterns. The quality of beef products has changed over the past several decades, and updated nutrient data are warranted as USDA Prime beef cuts become more available. In an effort to provide a complete nutrient profile for frequently purchased USDA Prime beef cuts, five USDA Prime cuts; strip loin steak, tenderloin steak, ribeye steak, top sirloin steak, and rib roast were collected from retail stores in six geographical locations over three collections for macro- and micronutrient analysis in both the raw and cooked state. The separable lean portion of all analyzed USDA Prime cuts qualified as a good or excellent source, providing 10-19% or at least 20% of the daily value, respectively, for protein, niacin, vitamin B12, selenium, phosphorus, and zinc per FDA labeling claim standards. There was not a significant difference in cholesterol content between any of the cuts, raw or cooked (p ≥ 0.44 and 0.34, respectively). The percent lipid in raw, separable lean portions of the rib roast and strip loin steak was significantly greater than the lipid portion in tenderloin and top sirloin steaks (p ≤ 0.01). Per USDA standards, the separable lean portions of tenderloin steak and top sirloin steak qualify as lean beef, containing less than 10 g total fat, less than 4.5 g saturated fat, and less than or equal to 95 mg cholesterol. The current study provides the most up-to-date nutrient analysis for USDA Prime beef cuts, helping consumers and health professionals better identify the role of high-quality beef cuts in healthy dietary patterns.

Smart customer service in unmanned retail store enhanced by large language model

In unmanned retail store, providing smart customer service requires two stages: understanding customer needs, and guiding the customer to the product. In this paper, we propose an end-to-end (Customer-to-Shelf) software service framework for unmanned retail. The framework integrates visual recognition technology to detect retail objects, large language models to analyze customer shopping needs and make proper recommendations. First, deep neural network based image recognition models are studied for implementing effective stock keeping units (SKUs) object recognition on the shelf. Second, a novel method is proposed to fine-tune large language models (LLMs) with limited training dataset. Metaheuristic approaches are used to optimize the mask locations in a low dimensional parameter space, resulting a more efficient parameter updating method for limited downstream data. Third, by facilitating an automatic analysis of customer preferences powered by large language models, we present a smart recommender system based on domain-specific knowledge, which completes the Customer-to-Shelf software service framework. Experimental results show that our proposed fine-tuning method, is more efficient than other state-of-the-art training methods for limited downstream domain dataset. Using fine-tuned large models, we can successfully create a seamless shopping experience for customers by understanding personalized needs and providing shopping advice in the unmanned retail store.

Supply chain visibility and integration in the age of the Internet of Things: a retail perspective

Purpose This study aims to assess the use of the Internet of Things (IoT) in retail stores to improve supply chain visibility and integration.Design/methodology/approachThis study employed a qualitative methodology with data collected using semi-structured interviews from a sample selected using purposive sampling. The population consists of 48 employees, of which 6 were selected for the sample as they worked directly with IoT and supply chain issues. Participants were from a SPAR franchise store (Samenwerken Profiteren Allen Regalmatig).Findings Thematic analysis was used to analyse the transcribed data from the interviews. The themes identified include supply chain visibility, supply chain integration and IoT. The findings indicate that the main IoT used is an organisational-wide system, the SIGMA (SPAR Integrated Goods Management Application) system. Other technologies that aid supply chain visibility and integration are geotags, the internet, WhatsApp social media applications, emails and scanners.Practical implications From the findings, this study recommends that IoT systems should be frequently updated to reflect current trends and that IoT systems should enable the integration of small and medium Enterprises (SMEs) suppliers.Originality/value The Fourth Industrial Revolution has ushered in new technologies that revolutionise business operations. Among these technologies is the IoT, which has ushered in a new connectivity area. However, there is little research on the use of IoT for supply chain visibility and integration in the South African retail sector. It provides sector-specific insights and recommendations for retailers, which might not be covered in general supply chain management literature.

Determinants of the continuance use of smart shopping carts: Findings from PLS-SEM and NCA

This study integrates theory of consumption value, cognitive dissonance theory, and technology acceptance model to understand shoppers’ continuance intention to use smart shopping carts in retail stores. The survey instrument was circulated online to shoppers who have already experienced smart shopping carts in retail stores. 343 respondents were considered for the final analysis using partial least squares structural equation modelling and necessary condition analysis. Perceived value, perceived enjoyment, technology anxiety and compatibility were used as antecedents, perceived convenience as a mediator and continuance intention to use smart shopping carts as an outcome. The results of the study indicate that technology anxiety and compatibility are necessary and must-have factors for perceived convenience in using smart shopping carts. Additionally, perceived enjoyment, perceived value and perceived convenience are necessary and must-have factors for the continuance intention to use smart shopping carts. However, perceived value is identified as an unimportant factor influencing shoppers' continuance intention to use smart shopping carts in retail settings.