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Convenience stores are essential facilities for older people living in cities, but there is a lack of discussion about the relation thereof to care for older people. An emerging phenomenon in Japan, one of the countries with the most rapidly aging population, is that convenience stores are also becoming a form of care infrastructure. In this article, I focus on this phenomenon in a time of care crisis by examining convenience stores in Tokyo, Japan, through the framework of care infrastructure. I combine descriptive statistics, government and corporate reports with interviews with 15 older adults in Tokyo to assess the potential and challenges of convenience stores as entities that contribute to their care. The findings of my study indicate that convenience stores may contribute to the care of older people because of their proximity, multifunctionality, sociality and sheltering nature, while challenges relate to affordability, equity and fairness. In the conclusion, I offer some suggestions regarding opportunities for and challenges to expanding care in aging cities by rethinking the potential of convenience stores as social and physical infrastructure. [ABSTRACT FROM AUTHOR]

Purpose – This study evaluated the determinants of augmented reality (AR) adoption in Malaysia's travel and tour operator sectors through an integrated technology-organization-environmental (TOE) and diffusion of innovation (DOI) model. Design/methodology/approach – The TOE and DOI were considered the primary theoretical models but are combined and extended by including few additional variables. Data were collected from 220 respondents of travel and tour operating businesses in Malaysia and analyzed by applying PLS structural equation model technique. Findings – The empirical results established that perceived cost, relative advantages, complexity and compatibility, observability, competitor pressure, value alignment, customer pressure, and trialability are positively connected with the behavioral intention except for external support. The results reveal that value alignment partially mediates the association between relative advantages and behavioral intention, complexity and behavioral intention, compatibility and behavioral intention, perceived cost and behavioral intention except in between trialability and observability. Originality/value – This research is unique as the value alignment construct is included in the model, and thus it fulfills the literature gap by adding the mediation construct. This study contributes to enhancing AR's understanding of the Malaysian travel and tour operator industry through the lenses of owners or managers. It offers an integrated model that combines the TOE and DOI models, rare in this sector, and can be replicated or extended with validated scales.

Cooperative-based Islamic retail businesses need to measure and improve their service performance to increase customer satisfaction to be superior in competitive markets. The adaptation of the SERVQUAL (service quality) measurement to the RSQS (retail service quality scale) scale has no sharia and co-operative dimensions. Therefore, the RSQS scale needs to be adapted to be SC-RSQS (Sharia_Co-operative_Retail Service Quality Scale) with the addition of sharia and cooperative dimensions. This adaptation has been validated by the panel of experts. On the other hand, SERVPERF (service performance) serves as a solution to the SERVQUAL weaknesses in measuring service performance. Satisfaction- and dissatisfaction-causing factors can be classified using Kano's Model. Records of consumer desires are needed to qualitatively fill deeper substances, which are analyzed using coding analysis. The integration of SC-RSQS in SERVPERF and Kano's Model was emphasized in this paper and was clarified using the coding analysis of customer records. This paper aimed to measure service performance, categorize customer requirements, and identify things that need to be considered in improving the performance of the 212 Mart cooperative retail store service in South Jakarta, Indonesia. The results show the level of satisfaction of cooperative members as the main consumers of this business is lower than non-cooperative members, 87% of customer requirements are in one-dimensional category, and the potential for customer dissatisfaction is higher than the potential satisfaction. 212 Mart must give cooperative members greater benefits than non-cooperative members, be more sensitive in providing services, and try to be more communicative with customers, especially cooperative members. [ABSTRACT FROM AUTHOR]

Cooperative-based Islamic retail businesses need to measure and improve their service performance to increase customer satisfaction to be superior in competitive markets. The adaptation of the SERVQUAL (service quality) measurement to the RSQS (retail service quality scale) scale has no sharia and co-operative dimensions. Therefore, the RSQS scale needs to be adapted to be SC-RSQS (Sharia_Co-operative_Retail Service Quality Scale) with the addition of sharia and cooperative dimensions. This adaptation has been validated by the panel of experts. On the other hand, SERVPERF (service performance) serves as a solution to the SERVQUAL weaknesses in measuring service performance. Satisfaction- and dissatisfaction-causing factors can be classified using Kano’s Model. Records of consumer desires are needed to qualitatively fill deeper substances, which are analyzed using coding analysis. The integration of SC-RSQS in SERVPERF and Kano’s Model was emphasized in this paper and was clarified using the coding analysis of customer records. This paper aimed to measure service performance, categorize customer requirements, and identify things that need to be considered in improving the performance of the 212 Mart cooperative retail store service in South Jakarta, Indonesia. The results show the level of satisfaction of cooperative members as the main consumers of this business is lower than non-cooperative members, 87% of customer requirements are in one-dimensional category, and the potential for customer dissatisfaction is higher than the potential satisfaction. 212 Mart must give cooperative members greater benefits than non-cooperative members, be more sensitive in providing services, and try to be more communicative with customers, especially cooperative members.

This research investigates the role of data science in understanding customer behavior and enhancing sales, focusing specifically on the application of Apriori and FP-Growth Algorithms at a retail store, Deli Point, in Labuan Bajo. It illuminates the impact of 'rubbish data' on transactional data analysis, emphasizing the need for robust data cleaning procedures to ensure accurate results. Utilizing the faster FP-Growth Algorithm, the study effectively analyzed customer purchasing patterns to identify optimal product combinations for sales improvement. It discovered that 'parsley local' and 'mint flores' items had the highest support with a value of 0.036, indicating that strategic placement of these items together could enhance sales. The rule between chicken leg bone, orange sunkist, and chicken breast boneless was found to have a high confidence value and a lift value higher than 1, implying a higher potential for these items to be sold when positioned near each other. This study contributes to understanding consumer behavior and provides insights for enhancing sales and competitiveness in the retail industry. An association rule involving 'chicken leg bone’, 'orange sunkist', and 'chicken breast boneless' demonstrated high confidence and a lift value above one, suggesting significant sales potential when these items are grouped together. This study not only contributes valuable insights into retail consumer behavior and effective product placement strategies but also underscores the transformative role of data science in optimizing sales and boosting competitiveness in the retail sector.

Point of Sale (POS) system in the business field, especially in the field of sales in retail stores is needed. This is because POS can replace business processes from conventional to systemized using electronic devices, namely computers. Toko Kafindra currently has not implemented a computerized business process. Therefore, this research implements a POS that can help Toko Kafindra in facilitating the management of business processes so that the retail store business can grow rapidly. This research uses a prototype model to facilitate the identification of user needs for the system to be built. The results showed that the Kafindra Store POS not only made it easier for the owner to know the outgoing goods but also could make it easier for the owner to know the incoming goods using the system of purchasing goods to suppliers. In addition, based on the results of the blackbox test on the system, the test results are valid and the system functions properly

The food industry, in general, and the retail grocery sector, in particular, have gone through an extensive transformation regarding sustainability communication. The retail grocery store is the stage on which in-store sustainability communication is triggered and incentivized. This paper focuses on the role of the store manager and is guided by the purpose to explore what roles and functions a store manager may perform as sustainability ambassador, and in what ways the dynamics between the central and store level may influence how sustainability is reflected and communicated in the retail store. The study draws on a qualitative and interpretative approach. The empirics are based on interviews with retail store managers in three Swedish grocery retailers. Through our empirical investigation, six different actions have been identified that both separately and in combination contribute to the field by giving a more nuanced view of what role and functions a store manager may perform as sustainability ambassador. [ABSTRACT FROM AUTHOR]

In today's world, where consumption is increasing rapidly, the designs of retail stores have gained importance with the increasing competition between institutions. One of the most predominant factors in the contact of the store with the customer is the spatial quality, which reveals the ability of the spatial features to meet user expectations. The study aims to determine the spatial quality indicators in retail stores and to expose the relationship between the importance and performance perception of these criteria among user groups. For this purpose, Importance-Performance Analysis (IPA), which has been a user-participated method and has powerful advantages in measuring service quality, was used in the study. In the first stage of the study, we determined the spatial quality indicators (functional, technical, and aesthetic) and subindicators by a literature review. The second stage is fieldwork performed in the determined study area, Koçtaş. At this stage, visual data of the study area was obtained, and 119 people (97 customers and 22 personnel) participated in the survey. In the third stage, IPA was used in analyzing the data. In the fourth stage, results were evaluated by supporting the visuals of the space. As a result of the study, the store was weak, especially in terms of aesthetic indicators, and significant differences were perceived by users between the importance and performance of spatial performance indicators. The study will lead up for research on examining the relationship between importance and performance in spaces with different functions by including the user in the process of determining and improving spatial quality. [ABSTRACT FROM AUTHOR]

AbstractProduct portfolio analysis is a critical aspect of small and medium-sized enterprises (SMEs) strategic planning and decision-making. It helps SMEs assess their existing product offerings, identify areas for improvement, and make well informed decisions about which products to keep, discontinue, or add to their portfolio. This type of analysis is crucial for SMEs as it enables them to optimize their product mix, allocate resources effectively, and respond to market changes, thereby ensuring growth and profitability. The objective of the research is to present a new product portfolio analysis tool that SMEs with a more efficient and effective way of evaluating their product offerings paying attention to those that cause a negative impact on performance. The Contribution Margin and Quantity Matrix (CMQ matrix) enables SMEs to gain a deeper understanding of their product mix, identify areas for improvement, and make informed decisions about which products to keep, discontinue, or add to their portfolio. This can lead to increased efficiency, better resource allocation and increased competitiveness, ultimately contributing to the success and profitability of the SME. The proposed instrument allowed decisions to be made after being applied in the analysis of the product portfolio of a retail store. The application of the proposed matrix allowed the analysis and decision making in relation to the product portfolio of an SME, facilitating an improvement in the performance indicators of the products studied.

In today's world, where consumption is increasing rapidly, the designs of retail stores have gained importance with the increasing competition between institutions. One of the most predominant factors in the contact of the store with the customer is the spatial quality, which reveals the ability of the spatial features to meet user expectations. The study aims to determine the spatial quality indicators in retail stores and to expose the relationship between the importance and performance perception of these criteria among user groups. For this purpose, Importance-Performance Analysis (IPA), which has been a user-participated method and has powerful advantages in measuring service quality, was used in the study. In the first stage of the study, we determined the spatial quality indicators (functional, technical, and aesthetic) and sub-indicators by a literature review. The second stage is fieldwork performed in the determined study area, Koçtaş. At this stage, visual data of the study area was obtained, and 119 people (97 customers and 22 personnel) participated in the survey. In the third stage, IPA was used in analyzing the data. In the fourth stage, results were evaluated by supporting the visuals of the space. As a result of the study, the store was weak, especially in terms of aesthetic indicators, and significant differences were perceived by users between the importance and performance of spatial performance indicators. The study will lead up for research on examining the relationship between importance and performance in spaces with different functions by including the user in the process of determining and improving spatial quality.

The study investigates the impact of panic buying on unplanned purchases at retail stores. Employing a quantitative approach with explanatory research, 210 respondents were surveyed to explore the relationship between panic purchases (independent variable) and unplanned purchases (dependent variable). The data analysis was conducted using the SPSS program version 26.00, and simple linear regression was applied. The findings demonstrate that panic purchases significantly influence unplanned purchases at retail stores. The anxiety and fear experienced by the community during the pandemic regarding their household necessities trigger panic buying. As a result of the urgency to fulfill daily needs and the availability of goods, individuals tend to engage in unplanned purchases when shopping at retail stores. The study highlights the connection between panic buying behavior and the tendency for unplanned spending in the context of retail shopping during times of heightened uncertainty and perceived scarcity. [ABSTRACT FROM AUTHOR]

The objective of this study is to evaluate a prototype local ventilation system (LVS) intended to reduce retail store workers' exposure to aerosols. The evaluation was carried out in a large aerosol test chamber where relatively uniform concentrations of polydisperse sodium chloride and glass-sphere particles were generated to test the system with nano- and micro-size particles. In addition, a cough simulator was constructed to mimic aerosols released by mouth breathing and coughing. Particle reduction efficiencies of the LVS were determined in four different experimental conditions using direct reading instruments and inhalable samplers. The particle reduction efficiency (%) depended on the position beneath the LVS, but the percentage was consistently high at the LVS center as follows: (1) > 98% particle reduction relative to background aerosols; (2) > 97% in the manikin's breathing zone relative to background aerosols; (3) > 97% during mouth breathing and coughing simulation; and (4) > 97% with a plexiglass barrier installation. Lower particle reduction (<70%) was observed when the LVS airflow was disturbed by background ventilation airflow. The lowest particle reduction (<20%) was observed when the manikin was closest to the simulator during coughing. [ABSTRACT FROM AUTHOR]

Maintaining assortment in a warehouse, distribution centre or retail store is expensive. We propose a method for assortment optimization that allows defining the top-performing products in the warehouse, distribution centre or retail store. It allows finding top-performing products in a given location using actual sales data or from concurrency when the sales data are unavailable. The developed method of product performance evaluation could be used by distribution companies to find the right pricing strategy. The method described also proposes how to improve the assortment in order to expand the business and help the distributor or retailer to meet his business objectives. [ABSTRACT FROM AUTHOR]

Efficiency management is increasing its importance in the improvement of the chain sustainability. As such, this study aims to assess the performance efficiency of retail stores in fashion industry. The integrated approach of Delphi and DEA techniques was employed to address the performance efficiency assessment problem. The Delphi method was used to define the input and output variables, whereas the DEA was applied to evaluate the performance efficiency. The proposed approach was then applied into a fashion company in Hochiminh city of Vietnam to assess its retail chain performance. The results showed that labour, operational costs, size of store, number of customers, and sales revenue are considered as input and output variables in the retailing performance efficiency evaluation. Besides, it is also concluded in the study that most of efficiency retail stores are located in the dynamic districts and the efficient stores can be at any size. The proposed approach verifies its usefulness in the retailing sector. Therefore, it can be applied to the performance efficiency of retail stores in all industries. In terms of theoretical contribution, the input and output variables proposed in this study may devote to the literature in the concept and assessment of the performance efficiency. Moreover, comprehensive and multi-variable assessment of retailing sector may bring lots of benefits not only to the decision-making units but also the authorities or association with constraint funds.

Water is a crucial resource for life, and it is increasingly scarce in many regions of the globe. In addition, retail water use is responsible for up to 19% of public water globally supplied. Hence, this study has set out to explore the technical and economic feasibility of rainwater harvesting systems as an alternative water source for a retail store located in southern Portugal. Water consumption data from 2018 to 2021 was collected from water bills, placing average monthly water consumption at around 400 m3. Next, rainfall data was collected from the nearest meteorological station, comprising 54 years of daily rainfall data between 1932 and 2008 with an annual average of 685 mm. The simulation of a rainwater harvesting system was performed, resorting to the mass-balance model. The optimal tank size was found to be 100 m3 considering simply the relation with the relative water savings variation on the graph relating the water savings with the tank size. Results show that the simulated rainwater harvesting system would allow saving 32–36% of the water consumed, despite the store's location in a dry climate, representing a financial gain of €330–372 per month. Findings suggest a substantial potential for the technical and economic feasibility of rainwater systems in retail stores, which makes them relevant solutions to achieve important water-savings in the retail sector, thus positively influencing retailers' direct water footprint. [ABSTRACT FROM AUTHOR]

Many retailers have low sales due to the difficulty in the purchase decision of their customers. Previous research shows the lack of studies on the impact of store interiors on purchase decisions. This study aims to find out various visual merchandising factors that affect purchase intentions at XYZ retail stores and focuses on visual merchandising itself, as well as store environment and customer inspiration factors that affect customer behaviour. The non-probability sampling technique with analysing 140 respondents using an online questionnaire with SMART PLS was used to conduct this research. The results show that customer inspirations directly influence customers' purchase intentions. Visual merchandising and store environment indirectly affect purchase intention as well, mediated by customer inspirations. The customer inspiration variable is in the good category in the XYZ store. It is recommended to use quick response in visual merchandising and develop a store environment virtually that can be connected to a customer's device. [ABSTRACT FROM AUTHOR]

Aim/purpose – Olfactory marketing is a phenomenon that is in the current trend of usage by marketing experts to ensure that consumers are more involved in the purchase decision-making process. This paper aims to review the studies involved in consumer purchase intentions influenced by fragrance and develop a framework for modeling consumer responses.

Aim: The aim of this paper is the efficient prediction of demand for Electronics Items in a Retail Store during festive seasons by adopting Novel ResNet Algorithm and its performance comparison over Deep Belief Network. Materials and Methods: At different stages, the Deep Belief Network and Novel ResNet algorithms were iterated in order to predict the accuracy percentage of accidents that occurred. Two sample groups are considered and tested, and G-power is a computation that includes two groups, alpha (0.05), and Power (80%). Results: It was observed that the Novel ResNet algorithm obtains an accuracy of 83.16% and the Deep Belief Network has 77.24%. This DBN appears to have a better significance of P=0.016 than the Novel ResNet, that is p<0.05 using the independent T-test sample for the analysis. Conclusion: This study contains analyses that target the sparsity in the income facts with the aid of converting a wide variety of product attributes. The result proves that the Novel ResNet Algorithm approaches predicting the retail store prediction during the festival season. [ABSTRACT FROM AUTHOR]

Aim: The research is about the Novel Deep Belief Network (NDBN) approach for Retail Store Sales Prediction during peak demand seasons and its performance comparison over K-Nearest Neighbour Technique (KNN). Materials and Methods: Deep Belief Network (N=10) and K-Nearest Neighbour algorithm (N=10) samples were considered based on the clinc calc online sample size calculator for predicting the accidents that happened in terms of accuracy. Two sample groups are taken into consideration and tested, G-power is the calculation that contains two different groups, alpha (0.05), power (80%), and environment ratio. Results: The Novel Deep Belief Network algorithm achieved 84.53% accuracy and K-Nearest Neighbour has 74.24%. This NDBN appears to have significance of p equal to 0.02 for the K-Nearest Neighbour, that is p less than 0.05 using independent sample T-test analysis. From the result, it proves that the Deep Belief Network approaches predict the retail sales store prediction. [ABSTRACT FROM AUTHOR]

Aim: The aim of this paper is to implement a Novel Convolutional Neural Network based has model for Sales forecast in an Electronic Retail Store during Festive seasons and a comparison of prediction accuracy with a Deep Belief Network. Materials and Methods: Deep Belief Network (N=10) and Novel Convolutional Neural Network algorithm (N=10), n is iterated at different times for predicting the accuracy percentage of accidents that happened. Two sample groups are taken into consideration and tested, G-power is a calculation that contains two different groups, alpha (0.05), and power (80%). Results: It was observed that the Deep Belief Network algorithm obtains an accuracy of 77.14% and the Novel Convolutional Neural Network has 84.86%. This Deep Belief Network appears to have a significance of p=0.019 than the Novel Convolutional Neural Network, that is p<0.05 using an independent sample forT-test analysis. Conclusion: The Deep Belief Network technique appears to have more significance than the Novel Convolutional Neural Network algorithm. The analysis generally works in a variety of end-use industries, and the results demonstrate that this strategy is important. The result proves that the Novel Convolutional Neural Network approaches to predict the retail sales store prediction. [ABSTRACT FROM AUTHOR]

Shelf space is one of the essential resources in logistic decisions. Order picking is the most time-consuming and labourintensive of the distribution processes in distribution centres. Current research investigates the allocation of shelf space on a rack in a distribution centre and a retail store. The retail store, as well as the distribution centre, offers a large number of shelf storage locations. In this research, multi-orientated capping as a product of the rack allocation method is investigated. Capping allows additional product items to be placed on the rack. We show the linearisation technique with the help of which the models with capping could be linearised and, therefore, an optimal solution could be obtained. The computational experiments compare the quality of results obtained by non-linear and linear models. The proposed technique does not increase the complexity of the initial non-linear problem. [ABSTRACT FROM AUTHOR]

Efficiency management is increasing its importance in the improvement of the chain sustainability. As such, this study aims to assess the performance efficiency of retail stores in fashion industry. The integrated approach of Delphi and DEA techniques was employed to address the performance efficiency assessment problem. The Delphi method was used to define the input and output variables, whereas the DEA was applied to evaluate the performance efficiency. The proposed approach was then applied into a fashion company in Hochiminh city of Vietnam to assess its retail chain performance. The results showed that labour, operational costs, size of store, number of customers, and sales revenue are considered as input and output variables in the retailing performance efficiency evaluation. Besides, it is also concluded in the study that most of efficiency retail stores are located in the dynamic districts and the efficient stores can be at any size. The proposed approach verifies its usefulness in the retailing sector. Therefore, it can be applied to the performance efficiency of retail stores in all industries. In terms of theoretical contribution, the input and output variables proposed in this study may devote to the literature in the concept and assessment of the performance efficiency. Moreover, comprehensive and multi-variable assessment of retailing sector may bring lots of benefits not only to the decision-making units but also the authorities or association with constraint funds. • An integrated approach of Delphi and DEA is an effective approach to solve the performance efficiency evaluation problem. • The proposed approach verifies its usefulness in the retailing sector not only in fashion industry but in other industries.. • Delphi was used to define the input and output variables, whereas DEA was applied to evaluate the performance efficiency. [ABSTRACT FROM AUTHOR]

Changes in the business environment and the entry of numerous competitors into the world market force business organizations to incorporate certain strategies that forecast the market changes and proactively restructure the organization's practices, technological capability, and processes to offer products/services within a short period without compromising quality and cost. However, business organizations depend on employees to perform the aforementioned activities to differentiate their offerings from their competitors. Hence, it is critical to focus on more agile and effective HRM practices that can help businesses thrive and flourish. The study aims to assess the implementation of agile HRM practices in the Indian retail industry using the multi-grade fuzzy method. Three enablers, six criteria, and fifty-eight attributes have been identified from the extensive literature review and expert opinion. The calculated overall agile HRM index of 4.49, which is in between the range of 4–5, reveals that the case retail store's focus on agile HRM practices is low. The results also found the case retail store's weaker attributes through Importance Performance Analysis and provided necessary suggestions for improvement. This research offers managers a framework for evaluating their store's success using agile HRM techniques. This study can assist retail store managers in identifying critical agile HRM practices for their businesses, and it also suggests that combining agile techniques with HRM can improve an organization's agility. [ABSTRACT FROM AUTHOR]

• A graph-based model of superpixels is introduced for segmenting gap/non-gap regions in the shelf images of supermarkets. • A shelf image is over-segmented into superpixels to create a graph of superpixels (SG). • The nodes and edges of a SG are uniquely encoded using our graph convolutional and Siamese networks. • A structural support vector machine is formulated with the SG for finding gaps in shelves. • Our annotations for three retail product datasets labelling gap/non-gap regions are released at https://github.com/gapDetection/gapDetectionDatasets. Automatic detection of empty spaces (gaps) between the displayed products as seen in the images of shelves of a supermarket is an interesting image segmentation problem. This paper presents the first known attempt to solve this commercially relevant challenge. The shelf image is first over-segmented into a number of superpixels to construct a graph of superpixels (SG). Subsequently, a graph convolutional network and a Siamese network are built to process the SG. Finally, a structural support vector machine based inference model is formulated based on SG for segmenting the gap and non-gap regions. In order to validate our method, we manually annotate the images of shelves of three benchmark datasets of retail products. We have achieved ∼ 70 to ∼ 85 % segmentation accuracy (in terms of mean intersection-over-union) on the annotated datasets. A part of the annotated data is released at https://github.com/gapDetection/gapDetectionDatasets. [ABSTRACT FROM AUTHOR]