Retail Areas Research Articles

ҚАЗАҚСТАНДАҒЫ КӨТЕРМЕ САУДА НАРЫҒЫНЫҢ ИНФРАҚҰРЫЛЫМЫ: ЖАҒДАЙЫ МЕН ДАМУ БАҒЫТТАРЫ

This article analyzes the key components of the infrastructure of the food wholesale trade market in Kazakhstan. The authors provide a comprehensive review of retail trade formats in a regional context and assess the level of provision of trading platforms for the population. The study examines the structure of legal entities in trade, employment in regions, service preparation centers, wholesale trade centers, retail areas of large facilities, markets in rural areas, and the technical equipment ofspecialized markets.Additionally, the operation ofcommodity exchanges and the issues of purchasing products for stabilization funds are also explored. The state continues to play a key role in the food market, and the authors note that the Government of Kazakhstan is actively working on the development of digital infrastructure in food trade. The analysis identifies several issues that require state intervention, as well as the need to improve logistics and intermediary services. The authors emphasize the importance of introducing modern technologies alongside the development of commodity exchanges and mobile trade.

Touristification and retail diversity: theory and evidence

This study explores the impact of touristification on retail diversity in neighbourhoods, presenting a species-area relationship model to demonstrate how tourism-driven changes can negatively affect local residents by displacing unique local retailers. Empirical regression analysis, using differences-in-difference (DID) models and neighbourhood clustering to define retail areas in Hong Kong, found that tourist-concentrated areas have fewer diverse high-street retailers. The result argues that the trend of touristification, which often leads to a decrease in retail diversity, could undermine the resilience of a tourism destination. This is evidenced by the noticeable downturn in the retail industry seen in many previously over-touristed cities after the pandemic. The findings prompt further research into tourism’s role in changing retail landscapes, particularly in touristified neighbourhoods.

Unraveling Urban Retail Realities: Assessing Revenue Shifts and Policy Effects in Seoul, South Korea, Pre- and During the COVID-19 Pandemic

The post-2020 revenue trends in Seoul’s retail areas, influenced by government policies to curb the epidemic, exhibit diverse impacts across regions. Progressing through three stages—imposing gathering restrictions, easing business limits with reinforced movement constraints, and relaxing epidemic control—the measures, while uniformly applied, yield varied effects based on retail area characteristics. Using Dynamic Time Warping Clustering, this study assessed 1637 Seoul retail areas over 45 months, categorizing revenue changes into highly grown, grown, recovered, and stagnated types. Areas with increased pre-pandemic revenue displayed lower F&B sector proportions, higher sales/experiential sector proportions, and increased spending by 30s/corporate entities. These areas were characterized by lower-income residents and reduced accessibility to public facilities. Conversely, areas with high 20s consumption, lower corporate demand, and proximity to crowd-pulling facilities exhibited lower revenue recovery resilience. The study emphasizes the need for effective urban spatial management to facilitate the recovery of elastic retail area amid mobility and interaction constraints, advocating for fine-tuned measures to minimize pandemic-induced economic impacts on urban retail areas.

Building Sustainable Business through Omnichannel Retailing

The retail business is evolving rapidly, and this is happening as a result of changes in consumer demand and behavior. Omnichannel has transformed traditional retailing in every manner. It also altered the consumer's behavior, as they use more than one channel and different touchpoint throughout their purchasing journey now, than they did earlier. Numerous researchers and academics have also indicated that the seamlessness is one of the distinctive and significant characteristics of the omnichannel that, in comparison to other elements, has the greatest impact on consumer behavior. Moreover, in today’s informed and educated markets, consumers are more than aware and sensitive towards sustainability and environment- friendly practices and hence, increased pressure is being faced by companies to incorporate green practices, not just in production and manufacturing, but also in operations and supply chain activities. The concept of omnichannel is still in its preliminary stages of development which formed the groundwork for the primary goal of this research, i.e., to understand the omnichannel retailing. Furthermore, the article aimed to gain an understanding of the diverse elements that influence omnichannel retailing. Lastly, the study aimed to identify the contributions of omnichannel retailing towards sustainable business development. Systematic review of literature was adopted as the methodology employed in the present work and most of the insights in the paper were obtained from secondary sources published between January 2015 and December 2022. The significant addition of this work is to the advancement and improvement of knowledge in the areas of omnichannel retailing and its contribution towards sustainable business development.

Geographies of touristification of consumption spaces: How retail capital shapes the effects of tourism on shops, services and hospitality businesses

This study proposes a framework to measure touristification of consumption spaces, consisting of concentration of retail capital, business displacement and standardization of the consumption landscape. This framework is tested using business registration data and rent price estimates for consumption spaces in Amsterdam between 2005 and 2020. Touristification emerges from concentrations of retail capital and standardization, but occurs without causing significant business displacement. A cluster analysis identifies different variations of touristification. Besides the more typical cases these include nightlife areas, gentrifying consumption spaces and specialized retail areas. This suggests that local contingencies cause consumption spaces to respond differently to increasing tourism.

Optimizing shared bike systems for economic gain: Integrating land use and retail

This study explores the optimization of shared-bike station locations, emphasizing the cycling role in low-carbon mobility and local economic revitalization. A unique aspect of this research is the incorporation of the retail activity index in determining station locations, land-use mix, transit proximity, and population and employment densities. A novel weighting method, combining the multi-criteria decision method “Criteria Importance Through Inter-criteria Correlation (CRITIC)” with Ensemble-based predictive algorithms (Random Forest, XGBoost, Gradient Boosting), was developed to evaluate these factors. Using a geographic information system-based spatial model, this study conducted a suitability analysis by applying these weights to assess and propose bike station sites. The findings from the Seoul case indicate a balanced land-use mix, a low number of transactions linked to cyclists, and a significant gap in multimodal transport integration. The weighting results revealed a high priority for transit proximity and retail activity in station placement. Suitability scores across districts revealed significant variability, suggesting the need for greater integration of cycling policies into urban planning. High-scoring districts, such as Gangnam-gu and Seocho-gu, offer insights for improvements in less suitable areas. This study advocates expanded cycling planning, focusing on enhancing access to public transit and retail areas.

Greened shopping spaces and pedestrian shopping interactions: the case of Christchurch

Greened shopping spaces and pedestrian shopping interactions: the case of Christchurch

Microscopic modeling of attention-based movement behaviors

For transportation hubs, leveraging pedestrian flows for commercial activities presents an effective strategy for funding maintenance and infrastructure improvements. However, this introduces new challenges, as consumer behaviors can disrupt pedestrian flow and efficiency. To optimize both retail potential and pedestrian efficiency, careful strategic planning in store layout and facility dimensions was done by expert judgement due to the complexity in pedestrian dynamics in the retail areas of transportation hubs. This paper introduces an attention-based movement model to simulate these dynamics. By simulating retail potential of an area through the duration of visual attention it receives, and pedestrian efficiency via speed loss in pedestrian walking behaviors, the study further explores how design features can influence the retail potential and pedestrian efficiency in a bi-directional corridor inside a transportation hub.

Satisfaction of International Tourists with Departure Services at Kilimanjaro International Airport: A Study in Tanzania

This study assessed the relationship between airport departure non-processing service performance and international tourists' satisfaction at Kilimanjaro International Airport. A survey research design and quantitative approaches with stratified sampling and a 162 sample size were adopted. Data collection was done through closed-ended questionnaires. The questionnaires were distributed to tourists and picked after being filled up. Respondents’ responses were based on a five-point Likert Scale. Data analysis was done using IBM SPSS statistics version 21 and Partial Least Squares – Structural Equation Modelling using SmartPLS 3 software with the help of SmartPLS3 software. The study showed that airport departure facilities were directly and significantly associated with international tourists' satisfaction. This implies that the relationship exists in real life, and any effort to disregard the assessment of these facilities may disturb tourists' satisfaction and lead to untrustworthiness. Moreover, airport departure accessibility and departure retail areas showed an insignificant association with international tourists' satisfaction, implying that no relationship exists in real life. The study recommends that indicators for the constructs with direct relationships be treated as significant factors. However, airport operators should equally monitor service performance to achieve the highest tourist’ satisfaction in all three constructs to make tourists loyal since any service compromise can interrupt tourists' satisfaction. The findings have economic significance in improving tourism performance and airport service management.

USE OF MACHINE LEARNING TOOLS AND PYTHON LIBRARIES FOR PREDICTION THROUGH REGRESSIONS

The purpose of this work is forecasting the average check amount depending on the time spent by customers in the retail area and forecasting the average check amount based on seasonal demand characteristics considering the constant annual price growth. Forecast methods were analysed. The use of Python libraries was considered. The code was developed for solving the above-mentioned forecasting tasks through linear, polynomial and random forest regressions, specifically, the search for the dependence of the average check amount on the time spent by customers in the retail area and the dependence of the average check amount on seasonal price fluctuations over several years. A comparison of the results of linear and polynomial regression was made under conditions of smaller or larger volumes of the input data, explanations were provided regarding the appropriateness of choosing one or the other when modelling non-cyclical processes and why the random forest model provides adequate results for cyclical processes. The source code and examples of input data were shared for public access. Scientific novelty lies in the ways of applying regressions for modelling and forecasting the average check amount depending on the time customers spend in the retail area as well as the average check amount depending on seasonal demand characteristics with consideration of constant price growth. The selected examples of cyclical and non-cyclical economic phenomena are the most common ones, and practitioners face similar tasks daily. Therefore, the results of this work provide them with ready-made solutions that require minimal adaptation to practical needs. Additionally, it demonstrates the feasibility of deploying them in the AWS cloud environment and the potential for integration with various data sources and other information systems.

Machine Learning Driven Smart Transportation Sharing

In many urban areas, traffic congestion has become one of the most challenging issues of modern life, resulting in detrimental effects on the environment, productivity loss, fuel wastage, and longer travel times. As a solution, people are increasingly turning to shared transportation modes due to the convenience of multi-modal journeys facilitated by smart transportation systems. The last mile problem refers to the fact that, in large cities, buses and trains deliver passengers to transit stations close to retail and job areas, leaving them needing another form of transportation to reach their final destination. By promoting the use of public transportation and addressing this issue, a smart bike-sharing system can contribute to reducing traffic congestion. The study presents a review of various methods that are associated with the designing of the bike sharing system and suggests a model incorporating various methods to derive solutions, with a focus on utilizing clustering algorithms for the analysis of the provided time series dataset. The study reveals that the application of algorithms such as the K-Means algorithm, Fuzzy C-means, etc. would be very effective in visualizing the resulting clusters and improve the forecasting accuracy.

Shifts in property crime patterns during the COVID-19 pandemic in Mexico

Abstract Objectives To estimate the dynamic effects of the COVID-19 pandemic on property crime in Mexico. We do so for a longer time horizon than the existing literature and for two types of property crime: on-line and on-site. Methods A retrospective ecological analysis during the COVID-19 pandemic using an event study methodology. This paper uses administrative data from Mexico’s National Public Security System from January 2017 to December 2022. Our data is structured as a monthly series covering all 2457 Mexican municipalities. Results We find heterogeneity in the pandemic’s impact by type of property crime and a dynamic, permanent effect for both types of property crime. Namely, our results point to a drop and quick recovery of fraud—property crime mostly committed on-line—, which in the medium run surpasses pre-pandemic levels by 44%. Further, our results point to a significant drop in robbery, theft, domestic burglary, and motor vehicle theft—all property crimes committed on-site—, with a slight recovery after the end of the national lockdown, even though rates for these crimes never reached pre-pandemic levels. Conclusions The 2020 pandemic caused a permanent shift in property crime from on-site to on-line spaces. Potential mechanisms point to disruptions in mobility in retail and recreational areas, residential zones, and workplaces as important mediating factors.

PESTICIDE RESIDUE SCREENING IN CITRUS FRUITS BASED ON GAS CHROMATOGRAPHY-TANDEM MASS SPECTROMETRY AND HEALTH RISK ASSESSMENT

Lately, there is maximum concern in most states, all over the world, regarding the levels of pesticide residues in food products, considering their chemical properties with direct implications on human health. Many studies have shown that the adverse effects of cumulative exposure to multiple pesticide residues are far more severe than any single exposure. Statistically, the number of food alerts generated by the presence of pesticide residues in fruits on the market, between 2017 and 2021, as well as the situation related to the number of imports and intra-EU trade that took place during the same period was highlighted. This study aims to analyze pesticide residue levels in citrus fruits (i.e., lemons, grapefruit, and orange) imported from non-EU and EU countries, comparative with maximum residue limits (MRLs) provided by Regulation 2005/396/EC, to assess if intake levels pose a long-term risk to human health. The citrus samples collected from ten markets (retail and storage areas) in Romania, were prepared according to the procedure provided by EN 15662:2008 standard. The concentration of pesticide residues from citrus samples was determined by Gas Chromatography-Tandem Mass Spectrometry (GC-MS/MS). The results obtained by GC-MS/MS showed that from 52 citrus samples, 41 samples contained pesticide residues with values between 0.005 and 2.700 mg/kg, and several samples contained forbidden active substances (e.g., spirodiclofen and o-phenylphenol). The pesticide detection rate of the samples was 78.84%. The most frequently detected pesticides according to obtained results were imazalil, thiabendazole, pyrimethanil, pyraclostrobin, fludioxonil, as well as spirodiclofen and o-phenylphenol. The samples with the most detected active substances are from imports outside of the European Union. In addition, in several samples, simultaneously occurred four or even five mixed pesticide residues, hazardous to human health. This study shows that the presence of pesticide residues is constant in citrus fruits due to phytosanitary treatments carried out on crops in the development phase as well as on fruits in the storage phase treatments (e.g. insecticides, fungicides, etc.).

Retailing in India: Promulgation and Confrontation

The blast in India's retail area has fascinated numerous players-both at the public and global level-to receive the rewards of development in the retail business. The upsurge in the retail business has seriously changed the whole idea of shopping as far as the most recent organizations that are embraced and furthermore by virtue of customer purchasing conduct. There were days when buyers had a more independent attitude. Global brands where unfathomable and there was no openness of the assortments presented by the worldwide players. Shopping was more viewed as an action or an awkward undertaking where it was simply done to satisfy ones needs. Be that as it may, presently the circumstance appears to have taken a fast turn where in the wake of opening of the economy and passage of MNCs, shopping is appeared to be more as a joy and involvement in a wide assortment of items to browse the accessible. The blast of present-day retail design is clear from the rambling retail outlets, multistory shopping centers with amusement and food all under a solitary rooftop, stores, and hypermarkets, every one of them making shopping a pleasurable encounter. The monetary push of the 90's as confirmed in vigorous GDP development, more grounded money stores and dynamic market and working climate are impelling India on a direction of outstanding development in the area of retail exchange. The post advancement has seen retail arise as a dawn area. The financial advancement and expanded buyers mindfulness have given a driving force to retail change

Prediction framework for parking search cruising time and emissions in dense urban areas

AbstractThe growing need for temporary pickups/drop-offs and commercial deliveries is crowding out the already inadequate on-street parking spaces designated for car trips, deteriorating the phenomenon of parking search. This paper: (1) uses empirical data and conducts descriptive and comparative analysis using a spatial lag model to analyze the factors influencing average cruising time (ACT) related to parking search, and (2) proposes a novel framework to predict grid-based ACT and to estimate average emission metrics (AEM). The study inputs an aggregated GPS dataset in a 6-month period to the framework and uses New York City and Los Angeles as case study cities. The descriptive and comparative analysis results support the spatial spillover effect of parking search and reveal that residential area, retail area, accommodation, and food services (hotels, restaurants, bars, etc.) employees are the most significant influencing factors on ACT and that temporary pickups/drop-offs and commercial delivery are also unneglectable sources of parking search. The prediction results show a concentrated distribution of ACT in New York City due to private vehicles’ spillover of parking searches. Los Angeles exhibits a relatively high degree of overlap between parking hotspots and emission blackspots, particularly in areas with intense truck activity, further substantiating the close relationship between truck activities and elevated emissions. Following the key findings, the paper proposes several policy recommendations. In practice, this prediction framework can ingest short-term data to provide ACT prediction maps to identify parking hotspots and emission blackspots.

Pengendali Robot Pebisnis Menggunakan Teknologi Virtual Realty

In this study, the creator highlights research regarding one of the advancements in human-made conscious innovation, especially robots. The progress of robots is very complex and currently similar to humans. The examination technique used is to use a written survey by looking at books, diaries and other writings that can be used as reasons for research, with educational provisions it will build scientists' insight and develop information about the problems raised in the research. . In certain countries, robots are widely used and are starting to replace human tasks, for example in Japan, robots are widely used in cafes and accommodation areas. By utilizing robots, human work begins to decrease. This exploration creates opportunities if robots are used in retail or shopping areas, with this system providing suggestions for the advancement of mechanical technology in Indonesia.

IMPLEMENTASI SYSTEM MONITORING LINK OPTICAL LINE TERMINAL ICONNET BERBASIS ZABBIX SECARA REAL TIME

Internet services are widely provided by many internet network provider companies, one of which is Indonesia Comnets Plus (ICON+) which is an internet network provider with fiber optic infrastructure that has a service called Iconnet. Iconnet is a high speed prepaid internet service using the latest fiber optic technology that is reliable and stable for retail and residential areas. One of the problems that exist in the Iconnet internet network service is about the problems that exist in its network devices, one of which is the lack of supervision of the Oprical Line Terminal (OLT) so that it remains in good condition or there is no loss for internet network distribution where the device directly leads to the customer. In order to avoid these problems, this final report will design an OLT monitoring system in the Iconnet service, especially on the Zabbix-based link so that it can be monitored through notifications via Telegram or directly with Zabbix. It is hoped that the monitoring system that will be created will run smoothly according to the features that have been planned so that it can make it easier for workers at PT ICON+ to efficiently handle problematic OLT.

Factors Influencing Customer Preference towards Organised Food Retailing

In India the scope of organized food retailing has increased in the last few years, offering ample amount of opportunities to Indian business. Due to large consumer base, India provides an opportunity for their retailers all over the world to sell their products in India. In any business, change is the only permanent thing. Consumers prefer modern retail stores over the conventional and traditional stores. This has resulted in a major change in consumer behaviour. After considering the important changes in the consumer scenario in India, especially with regard to the present changing pattern in organized retail stores, the researcher has decided to study on consumer behaviour in organized retail industry with reference to organized food retail. This study has been focused on the Bangalore region which is a fast growing industrial belt in South India. It provides a guideline for further research in the area of organized retailing. This study gets importance because in this study, the consumer awareness, factors influencing consumer behaviour, marketing strategies, promotional mix, benefits and problems faced by the consumers and opportunities for the departmental stores in this area have been studied. This research is also getting importance because it aims to identify the consumer response and decision making behaviour in organized food retail. It also shows the future scenario of organized retailing keeping in view of current perspective.

Maximizing non-aeronautical revenues in airport terminals using gate assignment and passenger behaviour modelling

Airports must ensure that their operations can efficiently adapt to the emerging needs considering both the passenger experience and their economic viability. One way to achieve this is by optimizing the airport operations, aiming to maximize revenue levels considering operational objectives and passenger requirements inside the airport. This study presents an original mixed-integer linear programming model (MILP), which combines the gate assignment problem with passenger behaviour modelling. First, a survey was conducted to collect relevant information to model passenger behaviour and the purchases conducted in a terminal, leading to the estimation of discrete choice models that quantify the probability that a passenger makes purchases of certain levels at the terminal according to their flight type (departure, arrival or transfer). Then, the proposed MILP model assigns gates which would expectedly increase the airport non-aeronautical revenues at the terminal airport by matching flights and passenger gate categories to the most profitable gates, considering the proximity to the retail area, the walking distance needed to get to a gate in a specified time-horizon and the operational constraints of the airport. The application to the Lisbon Airport case study showed a potential increase of 8%–12.2% in revenues corresponding to 1732.7€ and 2967.3€ in half-an-hour time slots.

How has COVID-19 impacted the economic resilience of retail clusters?: Examining the difference between neighborhood-level and district-level retail clusters

The spread of COVID-19 greatly restricted physical and economic activities in global cities due to growing fears of infection and lockdown policies. Accordingly, the transfer of shopping activities from traditional markets to e-commerce has accelerated. Urban retail has substantially declined by competing with these disrupting factors, but resilience capabilities are known to vary by scale and regional characteristics. This study identifies which types of retail clusters were more resilient to the economic shock caused by the pandemic. This research focuses on the changes in online and in-store sales and how retailers recovered differently at the neighborhood and district levels in 2019 and 2020. This research compares the resilience of two types of retail clusters by calculating the loss of resilience and online adaptivity. The findings suggest that neighborhood-level retail areas were more resilient and bounced back in sales at a faster rate than district-level retail areas during the pandemic. These findings suggest that retail clusters are more resilient if they have steady populations and low-rent loads and can accommodate online shopping. The study contributes theoretical insights into how sales have changed and how e-commerce has increased the resilience of retail clusters throughout the pandemic by examining in-store and online sales.