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Digital retailing is omnipresent, such that shoppers increasingly interact with digital devices in physical stores. In service interactions involving the use of digital devices, shoppers attain novel forms of support, but they still need a means to achieve a sense of autonomy. To address this challenge, the current article reports on a qualitative analysis that reveals three main dimensions of phygital autonomy (visual, verbal, and kinetic) that relate to fundamental human senses and may enhance or undermine shoppers' perceived autonomy, due to their extension or restriction. By reviewing the concept of autonomy across distinct retail settings, this study also provides theoretical and practical insights for how to reconcile shoppers' autonomy dilemma, across their desires for freedom of action, freedom of choice, and human support. [ABSTRACT FROM AUTHOR]

For one-of-a-kind production (OKP) manufacturers adopting an engineer-to-order or make-to-order marketing strategy, it is very important to set an appropriate due date. We design an incentive-compatibility due-date quotation procedure to help OKP manufacturers obtain the rational due-date quotation from OKP customers. Based on the rational due-date quotation decision-making, the performance of an OKP shop floor controlled by load-based pull systems is evaluated in simulation. Our findings show that if the collaboration of due-date quotations and load-based pull control is effective, the order profit of OKP manufacturers will not be reduced when the delivery delay occurs. This study can provide more insights on order quotation decision-making and pull production control for OKP manufacturers. [ABSTRACT FROM AUTHOR]

This study proposes a unified, dynamic framework based on turnover event theory to evaluate the effects of dismissals, layoff announcements, and voluntary turnover on subsequent work-unit voluntary turnover. Applying our approach to 1,620 retail stores over 22 months, we show that modeling exit events as a dynamic and interdependent system adds to our ability to predict subsequent human capital outflow. Dismissals had the weakest total effect on subsequent voluntary turnover, layoff announcements had the strongest and most immediate effects, and voluntary turnovers had moderate but lasting effects. We also find that these three exit reasons each exhibit a distinct pattern of subsequent turnover intensity and longevity. Based on characteristics of work units in our setting, our results correspond to a cumulative worker-level average effect of 0.17 quits following dismissals, 0.23 quits following quits, and 2.2 quits following a layoff. We find that these "multiplier" effects are concentrated among workers of similar performance: high performer exits beget high performer quits, just as low-performer exits beget low-performer quits. Our findings suggest analyses offering individual-level estimates of turnover will generally underestimate the broader, work-unit level consequences of individual exit events on similar workers. [ABSTRACT FROM AUTHOR]

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]

Recognizing that it is a widespread crime, retailers in Turkey have adopted Crime Prevention through Environmental Design (CPTED) techniques to prevent shoplifting. Using data from 1,150 young adults residing in Istanbul, the current study investigates young adults' perceptions of such techniques, given that they are frequent shopping mall visitors by evaluating CPTED's six elements: territoriality, formal surveillance, informal surveillance, mechanical surveillance, access control, and target hardening. The findings showed that young adults perceive target hardening to be the most effective preventive technique. The paper discusses the implications for future research into preventing shoplifting through CPTED-based techniques. [ABSTRACT FROM AUTHOR]

Purpose: The online brand advocacy behaviors of omnichannel shoppers, who mainly rely on integrated brick-and-mortar stores (recognized as a vital channel for delivering a seamless shopping experience and meeting the dynamic needs of the shoppers), are still understudied. This study aims to investigate how integrated store service quality (ISSQ) may elicit both positive and negative emotions that contribute to a memorable omnichannel shopping experience and have an impact on shoppers' attachment to the store, leading to their exhibition of online brand advocacy behaviors (brand defense, brand positivity, brand knowledge sharing and virtual positive expression). Design/methodology/approach: The study is a cross-sectional, descriptive and quantitative investigation. The research participants were chosen using a purposive sampling technique. Using a validated self-administered questionnaire, data were gathered from 886 Indian omnichannel shoppers who often purchase at the integrated brick-and-mortar store. The proposed conceptual model was tested using Smart PLS software for partial least squares-structural equation modeling. Findings: The results indicate that positive and negative emotions mediate the relationship between ISSQ and memorable omnichannel shopping experiences, subsequently impacting omnichannel shoppers' attachment to the store and leading to online brand advocacy behaviors. The relationship strength perceived by shoppers significantly positively moderated the relationship between store attachment and different online brand advocacy behaviors (brand defense, brand positivity, brand knowledge sharing and virtual positive expression). Research limitations/implications: The study relied upon single cross-sectional data from the Indian population, where omnichannel retailing is still nascent. Originality/value: This study addresses the need to investigate the different emotions that arise while evaluating service quality in omnichannel retail purchase journeys leading to memorable shopping experiences. Emphasizing post-purchase behaviors like different online brand advocacy behaviors (brand defense, brand positivity, brand knowledge sharing and virtual positive expression), this study is the first to show that ISSQ might affect four different OBAs through memorable omnichannel shopping experience and the shopper's sense of attachment to the store. The moderating effect of relationship strength perceived by shoppers with the retailer on a few proposed hypotheses was also tested to give managerial recommendations. [ABSTRACT FROM AUTHOR]

Purpose: This research focuses on common misconceptions about the factors driving women to purchase footwear impulsively. Its primary objective is to explore how emotional and social triggers specifically influence women's purchasing decisions, contrasting with the traditionally rational consumer models. Design/methodology/approach: An online questionnaire was administered to a sample of women, yielding 199 useable responses. Findings: The findings reveal the key determinants of women's impulsive retail footwear purchases, which include self-regulation, hedonic motivations and the influence of the retail store environment. This research challenges the prevailing assumption that women's passion for shopping is driven solely by inherent characteristics and suggests that external factors substantially shape their impulsive buying behaviour. In summary, the stereotypical portrayal of women as compulsive retail footwear shoppers may result more from external stimuli and environmental factors rather than an intrinsic trait. Originality/value: This study improves the existing knowledge of women's impulsive buying behaviour by unveiling the determinants of women's impulsive footwear purchases and assessing whether prevailing stereotypes hold true. [ABSTRACT FROM AUTHOR]

This paper aims to understand public preferences concerning the amenities people prefer easy access to and how much time they would prefer to spend getting there. The empirical data draw from a national survey (1491 responses) in Aotearoa New Zealand. For amenity, we reveal citizens significantly prefer access to local shops and greenspace. For active travel time, 20 minutes was an upper threshold, regardless of mode, beyond which people are more likely to drive or not travel. We also find that women and those with limited mobility adapt travel behaviour the most between day and night, mainly due to safety concerns. [ABSTRACT FROM AUTHOR]

Purpose: The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers. Design/methodology/approach: The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers. Findings: The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data. Practical implications: The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment. Originality/value: This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors' knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity. [ABSTRACT FROM AUTHOR]

Purpose: In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping. Design/methodology/approach: This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions. Findings: Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping. Originality/value: This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption. [ABSTRACT FROM AUTHOR]

Most histories of Australian cultural life pin the start of consumer credit's popularity to the 1950s and the heady days of the early long boom. This article reveals the longer history of consumer credit in Australia. Middle-class Australians have long made use of forms of credit provided by retailers such as monthly accounts to supplement their incomes, take advantage of special offers, deal with unexpected expenses, or indulge impulsive desires. Those with more limited and less regular incomes, working-class families unable to secure credit from banks or department stores, also became enmeshed in credit culture, but through a different route. An early form of retail credit – the cash-order system – played a crucial role in preparing working-class consumers for the postwar boom in credit culture. Emerging at the beginning of the twentieth century, the cash-order system provided a bridge between older forms of working-class retail credit such as the tick and the slate, and modern forms such as the department store budget accounts that would become widely available after the Second World War. [ABSTRACT FROM AUTHOR]

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

Neighbourhood commercial centres (NCC) are dynamic hubs that provide essential goods, promote community bonds and drive economic growth. Despite numerous studies on shopping behaviour, there remains a notable gap in understanding how transportation and shopping centre-related factors collectively shape the attractiveness of the NCCs, especially in developing countries like India. This research aims to understand why some NCCs outperform others in terms of attractiveness. This study proposes the neighbourhood commercial centre attractiveness index (NCCAI), which is developed by collecting 455 samples from 13 NCCs with the help of a primary survey to understand how different factors influence the attractiveness of NCCs in the Indian planned city context. The study used principal component analysis (PCA) and identified five major components that significantly contribute to NCC's attractiveness. Further, the weightage of the components was determined through two distinct approaches: one based on PCA results and the other utilising the analytic hierarchy process (AHP) with expert opinion data. Finally, the more reliable weights from these two methodologies were selected using analysis of covariance (ANCOVA). The NCCAI can help urban planners, store owners and retail managers, providing data-driven insights to enhance overall NCC attractiveness. The decomposable nature of NCCAI allows for component score breakdown, enabling planners and policymakers to allocate resources strategically. [ABSTRACT FROM AUTHOR]

This paper shows the effectiveness of labour transfers in addressing premature idleness caused by controlled order release. Controlled order release restricts order entry to the shop floor and is commonly employed in high-variety manufacturing where it results in benefits such as stable work-in-progress. However, it can increase waiting times when orders are blocked from release, while capacities are idling. This issue, known as premature idleness, negatively impacts delivery performance. Previous studies have primarily focused on addressing premature idleness through input control by releasing new orders to idling workstations. This approach overlooks the potential of output control during premature idleness, transferring labour to assist at other workstations in a dual resource constrained setting. Using simulation, this study demonstrates that output control significantly improves delivery performance—in terms of mean tardiness and percentage tardy—and reduces total and shop floor throughput times. Importantly, this result proves robust, even when the efficiency of the assisting worker is severely limited. Shop-level performance improves despite the efficiency loss of the worker. The impact of the where-rule is minimal, while the efficacy of the priority dispatching rule depends on the joint efficiency of collaborating workers. Finally, we show that combining input control and output control enhances performance, providing opportunities for further research on the role of both control approaches in high-variety manufacturing. [ABSTRACT FROM AUTHOR]

AbstractSocial robots, driven by cutting-edge technologies are designed to cater to various societal needs, facilitating complex human interactions involving multiple users and stakeholders. Their integration into daily life is anticipated to increase significantly. Within this context, the domain of shopping robots, which play a crucial role in enhancing and diversifying shopping experiences where human interaction is paramount, holds immense potential for development. This article aims to provide an overview of the current landscape of shopping robots and explore future research directions in this evolving field. Through this systematic review, key trends and insights in the field of shopping robots are identified, while also offering a categorization in the form of a 3D conceptual scheme, called the Public Space Robot (PSR) framework. The outcomes reveal significant developments over the past two decades (2002–2024), with the main concentration on developing and deploying mobile robots that offer functional or autonomous interaction for navigation assistance and customer service in shopping malls and retail stores. [ABSTRACT FROM AUTHOR]

The impact of family‐supportive supervision at the team level has largely not been explored. Since teams are the cornerstone of organizational effectiveness, it is critical to understand how family‐supportive managers can lead teams to achieve higher performance. We develop and test a team‐level moderated mediation model that unpacks the team‐level impact of Family Supportive Supervisor Behaviours (FSSB) on team performance. Drawing on Conservation of Resources (COR) theory, we hypothesize that a team's other‐focused emotional climate mediates the positive effects of team FSSB on team performance and that managers' relational job characteristics attenuate the positive influence of team FSSB. Results from a two‐wave, multi‐source study of 435 employees and their managers across 56 electronic retail stores support our predictions. These findings advance current multi‐level theorizing on FSSB by shedding new light on how and when family‐supportive managers can drive team performance. The implications for theory and practice are discussed. [ABSTRACT FROM AUTHOR]

This study explores into the levels of coliform contamination, prevalence of antibiotic-resistant bacteria, and the hygienic practices in goat meat retail stores. Goat meat from 10 retail stores was analyzed for E. coli , Salmonella , and S. aureus using serological and PCR methods. Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method. Data on hygienic practices were collected through a structured observational questionnaire. Pearson's correlation analysis was also employed to establish the relationship between hygienic practices and coliform loads. The average coliform loads on goat meat ranged between 0.88–5.04 log10 cfu/g. Our results revealed that 52% of examined goat meat was deemed unacceptable (>3.30 log10 CFU/g). The overall level of good meat handling practices among meat handlers in our study was 45.75%. Further, the study establishes a significant correlation between the level of food safety practices and coliform load. Hence, stores with higher hygienic practice scores exhibited lower coliform loads. The prevalence of S. aureus (44%) in goat meat was significantly higher (p < 0.05) as compared to E. coli (29%), and Salmonella spp. (20%). E. coli isolates displayed the highest resistance to penicillin (31.2%), Salmonella spp. to oxytetracycline (13.9%), and S. aureus to ampicillin (29.0%). Resistance was observed across selected antibiotic classes, particularly in beta-lactams and tetracyclines, with penicillin (78.5%) and oxytetracycline (64.5%) exhibiting notable resistance. Cephalosporin resistance was noted, with 48.4 and 33.3% of isolates showing resistance to cephalothin and cefpodoxime, respectively. Bacterial isolates also demonstrated resistance to phenicol antibiotics, including chloramphenicol (9.7%) and florfenicol (16.1%), respectively. Approximately 44.1% of bacterial isolates displayed multidrug resistance and MAR index ranged from 0.25 to 0.75. The study's findings reveal heightened levels of coliform contamination, the presence of pathogenic and multidrug-resistant bacteria in goat meat, and suboptimal meat handling practices in retail stores. The significance of improving food safety practices in retail settings is emphasized to ensure the safety of goat meat, a matter of increasing importance due to its growing demand globally. [ABSTRACT FROM AUTHOR]

The speedy progress of computer vision and machine learning engineering has inaugurated novel means for improving the purchasing experiment in brick-and-mortar stores. This paper examines the utilization of YOLOv (You Only Look Once) and DeepSORT (Deep Simple Online and Real-Time Tracking) algorithms for the real-time detection and analysis of the purchasing penchant in brick-and-mortar market surroundings. By leveraging these algorithms, stores can track customer behavior, identify popular products, and monitor high-traffic areas, enabling businesses to adapt quickly to customer preferences and optimize store layout and inventory management. The methodology involves the integration of YOLOv5 for accurate and rapid object detection combined with DeepSORT for the effective tracking of customer movements and interactions with products. Information collected in in-store cameras and sensors is handled to detect tendencies in customer behavior, like repeatedly inspected products, periods expended in specific intervals, and product handling. The results indicate a modest improvement in customer engagement, with conversion rates increasing by approximately 3 percentage points, and a decline in inventory waste levels, from 88% to 75%, after system implementation. This study provides essential insights into the further integration of algorithm technology in physical retail locations and demonstrates the revolutionary potential of real-time behavior tracking in the retail industry. This research determines the foundation for future developments in functional strategies and customer experience optimization by offering a solid framework for creating intelligent retail systems. [ABSTRACT FROM AUTHOR]

Recently, etomidate has been widely used as an alternative in illicit drug market. It is usually added to regular cigarette tobacco (commonly known as "cigarette powder") or mixed in e-cigarette oil sold through the Internet, retail stores, or entertainment outlets and other channels. An ultra-high performance liquid chromatography tandem mass spectrometry method was developed to quantify etomidate and etomidate acid in human blood and urine. The limit of detection (LOD) of etomidate and etomidate acid in blood is 0.5  and 2 ng/mL, respectively, and the lower limit of quantification (LLOQ) is 1  and 5 ng/mL, respectively. The LOD of etomidate and etomidate acid in urine is 1 and 2 ng/mL, respectively, and the LLOQ is 2  and 5 ng/mL, respectively. The precision, accuracy, recoveries, and matrix effects of etomidate and etomidate acid determinations in blood and urine met the requirements for methodological validation. The method was successfully applied to the identification and quantification of etomidate and etomidate acid in blood and urine of 62 forensic cases. The concentration of etomidate ranged from 1.52 to 8.41 ng/mL (positive cases, n  = 5) and the concentration of etomidate acid ranged from 2.76 to 112 ng/mL (positive cases, n  = 5) in blood. The concentrations of etomidate and etomidate acid in urine samples were 2.64–79,300 ng/mL (positive cases, n  = 59) and 6.11–518,000 ng/mL (positive cases, n  = 60), respectively. Therefore, the concentration of etomidate in blood and urine is mostly higher than that of etomidate. [ABSTRACT FROM AUTHOR]

Since 2020, many types of intoxicating cannabis products have entered the U.S. market. Hemp-derived intoxicating cannabis products, including hexahydrocannabinol and delta-8 tetrahydrocannabinol, pose concerns regarding their youth-oriented marketing, potency, and health effects. Some states have attempted to ban, restrict, or regulate their sale. However, the effectiveness of these laws and their enforcement is unclear. This study provides insights into the retail landscape of intoxicating cannabis products sold across the U.S. In November–December 2023, researchers systematically identified, called, and completed brief surveys with 520 U.S. vape shops: (n =10 per state, n =10 in District of Columbia, n =10 in Puerto Rico). The survey assessed the availability of 6 commonly sold intoxicating cannabis products. Data were analyzed by regulatory context. Analyses were conducted in 2024. A total of 74% of vape shops sold any intoxicating cannabis products. Intoxicating cannabis products were sold in 43% of shops in states with delta-8 tetrahydrocannabinol bans, 53% in states with substantial regulations (intended to support safe use), 90% in states with significant restrictions (intended to limit potency/availability), and 92% in states with limited/no regulations. Intoxicating cannabis products were sold in vape shops in each state except Washington and Alaska, both of which banned hemp-derived intoxicating cannabis products and had active retail of legalized nonmedical cannabis. Taking licensed dispensaries into consideration, intoxicating cannabis products can be purchased in retail stores located in all 50 states; Washington, District of Columbia; and Puerto Rico. Intoxicating cannabis products are widely available in vape shops, even in most states with relevant bans/restrictions. Enhanced laws, surveillance, and enforcement are needed. The 2024 Farm Bill and state laws should explicitly prohibit hemp-derived intoxicating cannabis products. [ABSTRACT FROM AUTHOR]

Person re-identification (re-id) attempts to match a person from the images of different time steps. Existing deep learning approaches either use appearance or geometry features for re-id which does not provide the required robustness because of higher intra-class similarity. Existing supervised re-id approaches utilize Convolutional Neural Networks (CNNs) and identity-labeled images to train, where the person images are taken by the sensors from a horizontal view. The horizontal view exposes the privacy of the people because of their facial appearance in the image. Moreover, person re-id includes new unseen people; however, CNN does not have the ability to identify the new unseen people because of a lack of continual learning. Privacy-preserved computer vision-assisted person re-id systems can benefit from visual appearance and geometry features extracted from top-view RGB and depth input. This paper presents the privacy-preserved person top-view re-id few-shot network which uses the appearance and geometry features. The EfficientNet is used for appearance-based features from RGB input, while PointNet is used to extract the geometry features from the point cloud which is made from the RGB-D image registration. Concatenated features from EfficientNet and PointNet are fed to the two-layer Bi-LSTM network for person identification. Finally, the whole network is converted into a few-shot network to achieve continual learning by removing the output layer and joining the similarity measurement unit. This approach is based on CNN and fine-tunes a TVPR/2 dataset acquired by using a top-view arrangement that is publicly available. The experimental results on TVPR/2 and GODPR datasets show that the proposed re-id network outperforms other state-of-the-art networks. [ABSTRACT FROM AUTHOR]

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Between 2015–2017, California local health departments assessed the retail environment in a convenience sample of small markets and convenience stores in low-income neighborhoods. This study examined differences in availability and quality of healthy foods and the physical retail environment by retailer participation in SNAP and WIC and by store type. Among 731 stores, we found that SNAP + WIC stores offered the greatest availability of healthy foods, high-quality produce, and healthful exterior marketing. Select associations were stronger among convenience stores than for small markets. Policy levers to incentivize SNAP and WIC participation among retailers can improve the neighborhood food environment. [ABSTRACT FROM AUTHOR]

Purpose: Despite the online shopping trend, many women still prefer in-store experiences for trying on and buying clothes. The body positivity movement endorsed by many brands implies that all women, even those with lower body appreciation, should feel included in this setting. However, studies have yet to quantitatively explore the mediating role of women's positive body image between clothing size and in-store experiences. To address this gap, this study examined the in-store experiences of 642 women from largely Western nations (Mage = 45.96, standard deviation (SD) = 9.31) who self-reported as straight-, mid- and plus-sizes and the mediating role of body appreciation. Design/methodology/approach: Participants completed online questionnaires with measures including clothing size, body appreciation, in-store experiences and preferences for in-store changes. Findings: Women of mid-size and plus-size were more likely than women of straight-size to report lower body appreciation, which led to a greater desire for guidance from staff about styles but less likelihood to approach them, higher discomfort going up a size and lower confidence trying on clothes. In contrast, straight-size women generally felt more comfortable and confident in-store clothes shopping. A direct link between clothing size and lower purchase intentions without in-store representation was found; however, body appreciation did not mediate this link. Preferences for in-store changes included better support from sales staff and more inclusive imagery. Originality/value: This study indicates that in-store clothes shopping may not feel like retail therapy for women who identify as mid-size or plus-size and experience low body appreciation. It highlights the need for comprehensive reform within the fashion retail industry by prioritizing inclusivity through better staff support and in-store representation for all sizes. [ABSTRACT FROM AUTHOR]

This study investigated the impact of accounting information systems (AIS) on the performance of retail stores, with Ok Gweru supermarket as the case study. The traditional manual accounting systems used by supermarkets have been replaced by computerized accounting systems due to globalization. However, these systems sometimes fail to process transactions quickly and are also vulnerable to criminal attacks. The study aimed to identify the reasons for these problems and provide solutions to address them in the retail industry. The research design involved a sample of 36 respondents, stratified according to their job roles. Data was collected using questionnaires. The study found a positive relationship between AIS and performance, as integrated systems that meet the basic reporting requirements of IFRS and GAAP can produce relevant information for sound economic decisions. Staff training to ensure user competency was found to be necessary, and supermarkets were identified as being at risk of cyber-attacks due to a lack of resources to protect their systems. It was recommended that these issues be continually discussed with employees to increase awareness of these malicious activities and how to counter them.

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. [ABSTRACT FROM AUTHOR]

By investigating emotional contagion in customer–employee interactions using the emotional facial action coding system, this study offers a means to separate primitive emotional contagion from its conscious counterpart. As an empirical validation of primitive emotional contagion and its impact on customer satisfaction, the multifaceted research approach, involving an experimental laboratory study and two field studies in hospitality and retail settings, reveals consistent findings. Additionally, the influence of emotional contagion on customer satisfaction is moderated by the esthetic appeal of the interior design. This work advances the theoretical understanding of the dynamics of primitive emotional contagion; it also offers practical insights regarding the importance of interior designs and busyness for enhancing service interactions. [ABSTRACT FROM AUTHOR]

Purpose: Emerging economies are dominated by an unorganized retail landscape, with complex sociocultural norms dictating the behavior of retailers and customers. The purpose of this paper is to explore the phenomenon of consumer embarrassment in an emerging marketing, India. Design/methodology/approach: This research adopts a grounded theory approach and undertakes 31 in-depth interviews with consumers in India. The data is analyzed inductively and iteratively simultaneously with data collection. Findings: The study uncovers that sociocultural normative influences, the retail environment's structural constraints, interaction-based buying processes and customers' perceptions play a role in eliciting embarrassment in traditional stores. The traditional format retailers play a significant role in evoking embarrassment and, surprisingly, also in facilitating coping. Contrary to the extant findings, purchasing embarrassing products online may not ensure anonymity and elicit embarrassment. The findings contribute to understanding the phenomenon of embarrassment in emerging markets. Originality/value: There is a dearth of research examining consumer embarrassment in emerging markets, with extant studies investigating the phenomenon in the modern retail setup of developed economies. The retail landscape of India is predominantly unorganized, with distinct transactional processes and physical characteristics that are starkly different from modern retail stores. Moreover, sociocultural normative forces have distinct influences on the informal setup of unorganized retail. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: Recent reviews on prism adaptation training (PAT) for visuospatial neglect concluded that it is ineffective. In our view, this conclusion goes too far. In this contribution, we discuss the limitations present in these reviews: the inclusion of right-sided neglect patients; failure to differentiate between patients with and without parietal lesions; ignoring results of line bisection or other tests. We argue that another aspect may play a role in the effectiveness of PAT: the extension of the task-work space. We show that using a workspace of more than 10° toward the contralesional side seems to improve the effectiveness of PAT. PAT still offers an important approach to treating neglect patients, and future studies should consider the extension of the workspace. [ABSTRACT FROM AUTHOR]

Growing popularity of self-service in retail stores and increasing associated shrinkage presents an urgent need for computer-vision-based product recognition in the area of self-checkouts. The article focuses on individual product recognition using automated workflow in images collected from retail store self-checkouts. The interest of this research lies exclusively in the recognition of barcodeless products—ones that present a challenge of being identified quickly and qualitatively at self-checkouts. Image sets representative of retail store product distribution do not exist as of the time of writing to the authors' knowledge. Images collected by exploiting self-checkout events often contain products partially covered by customer body parts, inside semi-transparent plastic bags, or not present in the area of interest. Due to the huge assortment of products that varies between stores and changes frequently, manual image labeling, filtering and long training time are unpractical. The proposed method investigates the need for automated steps to eliminate empty images and eliminate images where product visibility is unsatisfactory. Authors achieved 80.5±1.2% classification accuracy on a real-world dataset of 194 products using automatic workflow. The ablation studies proved the need for image filtering in both training and inference workflows. The neural network architecture tuned to the self-checkout dataset proved to outperform well-known networks: the suggested architecture's training time is a fraction of ImageNet's best EfficientNet and accuracy is slightly better. The suggested method generalization is proved on comparable products dataset Fruits 360, where 99.6% accuracy was achieved—comparable or better than other authors. [ABSTRACT FROM AUTHOR]

The last mile has to deliver goods at the right time for business logistics services to enhance the seamless customer service experience. The paper examines challenges confronting retail omnichannel distribution in achieving effective last-mile fulfilment operations processes in an apparel group (organisation phase). It investigates how the last mile for demand-driven store replenishment influences the level of retailers' order fulfilment (in full and on time) (environment phase). The paper also assesses integrated information systems' contribution to brick-and-mortar and virtual omnichannel distribution networks to improve timeousness, order accuracy and fill rate (technology phase). A mixed method was employed, with a quantitative methodology using frequencies and binomial testing combined with subjective thematic analysis of qualitative data from interviews. A hundred and seventy-five questionnaires were administered with a response rate of 85%. The main findings are that the current order fulfilment process aligned with the last mile is effective regarding the fill rate, lead time and condition of orders delivered via store economy and store express. [ABSTRACT FROM AUTHOR]

This study investigated the impact of accounting information systems (AIS) on the performance of retail stores, with Ok Gweru supermarket as the case study. The traditional manual accounting systems used by supermarkets have been replaced by computerized accounting systems due to globalization. However, these systems sometimes fail to process transactions quickly and are also vulnerable to criminal attacks. The study aimed to identify the reasons for these problems and provide solutions to address them in the retail industry. The research design involved a sample of 36 respondents, stratified according to their job roles. Data was collected using questionnaires. The study found a positive relationship between AIS and performance, as integrated systems that meet the basic reporting requirements of IFRS and GAAP can produce relevant information for sound economic decisions. Staff training to ensure user competency was found to be necessary, and supermarkets were identified as being at risk of cyber-attacks due to a lack of resources to protect their systems. It was recommended that these issues be continually discussed with employees to increase awareness of these malicious activities and how to counter them. [ABSTRACT FROM AUTHOR]

Marketing activities are of significant importance to business operations, as they are uniquely positioned to provide value to consumers. The marketing mix represents one of the strategic approaches employed to attain these organizational objectives. However, the company's sales data is only available for consultation in the archives. By understanding customer preferences and requirements, the company can readily develop an effective marketing strategy to compete with similar businesses. Accordingly, this study employs the neural network methodology to forecast sales based on the company's historical sales data. The research method employs a neural network due to its capacity for processing substantial data sets with flexibility. Moreover, the Root Mean Square Error (RMSE) must be employed to ascertain the precision of the utilized model. The findings of this study indicate that the discrepancy between the actual and predicted values is minimal, suggesting that the model is able to accurately represent the data. Similarly, the results of the RMSE (Root Mean Square Error) demonstrate that the model's accuracy is improving, with minimal values observed in each segment. A 4P marketing mix strategy may be employed to enhance the company's sales potential. Based on the findings of the research, it can be posited that the results of the prediction data set, the visual prediction results, and the RMSE using the Neural Network method can be utilized effectively and accurately to forecast sales and assist company owners and management in considering target sales levels in the future. [ABSTRACT FROM AUTHOR]

Purpose: Small retail stores in the luxury market face significant challenges due to fluctuations in market demand. This task turns challenging as it requires effectively coordinating and translating customer needs into specific requirements that align with retail goals and available resources. However, limited empirical research exists investigating how managers can address service value and quality attributes in small retail stores. This article aims to bridge this gap by investigating the role of quality function deployment (QFD) in improving market and quality requirements management in small retail stores. Design/methodology/approach: Based on the case study, a customer survey was initially conducted to gather information on critical characteristics valued in the luxury retail segment. QFD was used to assist the company in identifying and prioritizing key quality attributes to meet customer requirements effectively. Findings: The findings demonstrate that implementing QFD in small luxury retail stores empowers managers to identify previously neglected product and service quality aspects. The article shows that QFD informs organizational adaptations that align with the demands of the retail market, leading to an improved ability to meet customer expectations and enhance customer value through the development of enhanced products and services. The study showcases the efficacy of the tested methodology in effectively capturing and prioritizing both tangible and intangible customer needs in retail. Practical implications: Findings offer valuable insights to retail managers of small luxury stores, providing actionable market-oriented strategies. By implementing the recommended practices, managers can improve the store's competitiveness and better cater to the customer base. Originality/value: This study contributes to bridging persistent knowledge gaps by addressing the unique context of small luxury retail stores and introducing the application of QFD in this setting. The insights gained from this research are relevant to both retailing and quality management literature. Considering the growing prevalence of transformations in the retail industry, the study provides practical implications for retail managers in effectively navigating these changes. [ABSTRACT FROM AUTHOR]

Despite extensive research on retailers' price responses to demand shocks, much less is known about their non‐price responses. Using heterogeneity in timing, location, and magnitude of income and wealth shocks associated with the 2008 Great Recession, we explore how US retail stores adjusted product offerings under local demand shocks. We find that stores offer fewer products and varieties besides lowering prices. Using a structural demand model, we quantify the net welfare impact of the price and assortment adjustments. On average, the consumer welfare losses from variety reduction more than offset the welfare gains from price reductions. [ABSTRACT FROM AUTHOR]

This paper answers how changes in social media activity influence customers to visit nationally known, brick-and-mortar retail stores. We consider seven measures of social media activity within a Social Impact Theory framework and test under what context does online chatter about a brand lead to higher foot traffic to those brand stores. We use hierarchical linear regression to account for the random effects of brand and store heterogeneity, which is superior to ordinary linear regression. Despite wide variation, when brand mentions increase by one standard deviation—either in likes or disagreement—then next-day foot traffic to stores of that brand will increase by 0.04 standard deviations (3–4%). This modest but meaningful effect, however, fully dissipates within 1 week. The weak cross-brand effects show that social media has distinct and larger influence on brands individually rather than universally. Our approach is novel due to (1) the large scale of data, (2) the breadth of analysis, (3) the multi-level specification, and (4) in estimating global elasticities between changes in electronic word-of-mouth (WoM) communication about brands and changes in store visits of those brands. [ABSTRACT FROM AUTHOR]

We consider an order fulfillment problem of an omni-channel retailer that ships online orders from its distribution center (DC) and brick-and-mortar stores. Stores use their local information, not observed by the retailer, that can lead them to accept or reject fulfillment requests of items in an online order. We investigate the problem of sequencing requests to stores and inventory rationing decisions at the DC to minimize expected costs under uncertain store acceptance behavior and when items are indistinguishable in terms of shipping. First, under the scenario that stores are used only when the DC has insufficient inventory, we propose a Markov Decision Process formulation and analyze the performance of myopic policies that are preferable because of their interpretability. We show that the performance rate of a myopic approach that orders stores by cost only depends on the number of items in an order, which is small in practice. We also determine conditions for the range of acceptance probabilities for the myopic policy to be optimal for small-sized orders. Using optimality conditions for a special case of the problem, we develop an adaptive variant of the myopic policy, and propose a new degree-based strategy that balances shipping costs and acceptance probabilities. Numerical testing suggests that the best-performing sequencing policy is within 1% of optimality on average. Moreover, using two years of data from a large omni-channel retailer in North America, we observe that adaptive policies, albeit more complex, are beneficial in reducing costs and split deliveries if acceptance rates can be estimated accurately. Second, we determine when the retailer should ship from stores or ration the inventory at the DC. We show that for single-item orders, the optimal policy has a threshold structure, where, remarkably, the highest priority region is also subject to rationing. We then consider the novel multi-unit-single-item rationing problem, and leverage the structure of the single-unit model to develop a heuristic. We numerically establish the efficacy of rationing models and our heuristic. [ABSTRACT FROM AUTHOR]

Premium organic retailers are specialist retailers that exclusively offer organic products. Prior literature has not studied their entry, focusing instead on the impact of generalist store entry. This study examines the impact of premium organic specialist store entry on category performance at incumbent generalist stores for 47 packaged food and beverage categories. The results indicate that incumbent stores lose sales after a local organic store entry and that the impact of price on sales at generalist stores becomes stronger. The authors postulate that incumbent stores can reduce sales losses by reducing the relative distinctiveness of the entrant along three dimensions: variety, price–quality, and authenticity. Empirical results show that more variety in organic products, as well as more organic feature and display advertising, protect generalist stores from premium organic specialist store entry. Assortments composed of premium organic products are harmed less, whereas assortments in which organic products are subject to more frequent and deeper price promotions are harmed more. Furthermore, including products from an organic specialist brand in generalists' organic assortments offers additional protection. [ABSTRACT FROM AUTHOR]