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•Checkout process offered by a retailer is an important aspect of online shopping.•Retailers can use either a flexible or a restricted checkout to attract consumers.•Our paper offers guidance to online retailers on the appropriate checkout strategy.•Consumer and retailer characteristics impact the choice of checkout strategy.•A retailer may sometimes be better off choosing a distinct checkout strategy. [Display omitted] Growth in online retailing has driven retailers to focus on optimizing the consumers’ shopping journey. One of the most important aspects of online shopping is the checkout process offered by the retailer. This paper focuses on factors influencing retailers’ choice of providing either a flexible checkout or a restricted checkout option to consumers. We define a checkout strategy as flexible when consumers can purchase items in their shopping cart either as a guest or by logging into their account. In contrast, with a restricted checkout strategy, the consumers must log in to the account to make purchases. With a game-theoretic model and duopolistic framework, the current study identifies conditions in which online retailers might adopt symmetric strategies and those in which two ex-ante symmetric retailers might prefer asymmetric strategies. The analysis suggests that the relative proportion of privacy-conscious (PC) vs. convenience-conscious consumers (CC), additional utility due to account registration, reduction in transaction cost, and additional revenue due to targetability are the crucial determinants of the strategies adopted by online retailers. Specifically, we show that retailers adopt a restricted checkout strategy when additional revenues due to targeted advertising are relatively high. Retailers adopt a flexible checkout strategy when the proportion of CC consumers and additional revenues due to targeted advertising are relatively lower. Furthermore, an asymmetric equilibrium may also exist when the proportion of CC consumers is relatively high and additional revenues due to targeted advertising are in the intermediate range. Our modeling framework provides a consumer demand-based (rather than cost-based) justification as a plausible explanation for why we observe ex-ante identical retailers offering distinct checkout strategies.

Continual innovation and new technology are critical in helping retailers’ create a sustainable competitive advantage. In particular, shopper-facing technology plays an important role in increasing revenues and decreasing costs. In this article, we briefly discuss some of the salient retail technologies over the recent past as well as technologies that are only beginning to gain traction. Additionally, we present a shopper-centric decision calculus that retailers can use when considering a new shopper-facing technology. We argue that new technologies provide value by either increasing revenue through (a) attracting new shoppers, (b) increasing share of volume from existing shoppers, or (c) extracting greater consumer surplus, or decreasing costs through offloading labor to shoppers. Importantly, our framework incorporates shoppers by considering their perceptions of the new technology and their resulting behavioral reactions. Specifically, we argue that shoppers update their perceptions of fairness, value, satisfaction, trust, commitment, and attitudinal loyalty and evaluate the potential intrusiveness of the technology on their personal privacy. These perceptions then mediate the effect of the technology on shopper behavioral reactions such as retail patronage intentions and WOM communication. We present preliminary support for our framework by examining consumers’ perceptions of several new retail technologies, as well as their behavioral intentions. The findings support our thesis that shopper perceptions of the retailer are affected by new shopper-facing technologies and that these reactions mediate behavioral intentions, which in turn drives the ROI of the new technology.

This paper presents a smart checkout system designed to mitigate the issues of noise and errors present in the existing barcode and RFID-based systems used at retail stores’ checkout counters. This is achieved by integrating a novel AI algorithm, called Improved Laser Simulator Logic (ILSL) into the RFID system. The enhanced RFID system was able to improve the accuracy of item identification, reduce noise interference, and streamline the overall checkout process. The potential of the system for noise detection and elimination was initially investigated through a simulation study using MATLAB and ILSL algorithm. Subsequently, it was deployed in a small-scale environment to validate its real-world performance. Results show that RFID with the proposed new algorithm ILSL and AI basket is capable of accurately detecting the related items while eliminating noise originating from unrelated objects, achieving an accuracy rate of 88%.

Purpose - Mobile checkout in the retail store has the promise to be a rich source of big data. It is also a means to increase the rate at which big data flows into an organization as well as the potential to integrate product recommendations and promotions in real time. However, despite efforts by retailers to implement this retail innovation, adoption by customers has been slow. The paper aims to discuss these issues. Design/methodology/approach - Based on interviews and focus groups with leading retailers, technology providers, and service providers, the authors identified several emerging in-store mobile scenarios; and based on customer focus groups, the authors identified potential drivers and inhibitors of use. Findings - A first departure from the traditional customer checkout process flow is that a mobile checkout involves two processes: scanning and payment, and that checkout scenarios with respect to each of these processes varied across two dimensions: first, location - whether they were fixed by location or mobile; and second, autonomy - whether they were assisted by store employees or unassisted. The authors found no evidence that individuals found mobile scanning to be either enjoyable or to have utilitarian benefit. The authors also did not find greater privacy concerns with mobile payments scenarios. The authors did, however, in the post hoc analysis find that mobile unassisted scanning was preferred to mobile assisted scanning. The authors also found that mobile unassisted scanning with fixed unassisted checkout was a preferred service mode, while there was evidence that mobile assisted scanning with mobile assisted payment was the least preferred checkout mode. Finally, the authors found that individual differences including computer self-efficacy, personal innovativeness, and technology anxiety were strong predictors of adoption of mobile scanning and payment scenarios. Originality/value - The work helps the authors understand the emerging mobile checkout scenarios in the retail environment and customer reactions to these scenarios.

Mobile Social Commerce (MSC) is the present and the future of e-commerce; and a growing topic of research interest. However, despite its numerous current abilities and its prosperous future prospects there has been slightly investigated so far. In order to fill this research gap, this empirical study aims to model and examine the factors that impact individuals’ behavioral intention on adopting MSC. In specific, it focuses on a comparatively new service of Instagram, the checkout option; and investigates m-users’ behavioral intention towards this operation in a country where this service is not available yet. The study presents a holistic acceptance conceptual model in the context of MSC that combines the UTAUT scheme, the innovation characteristics of the DOI theory (i.e., compatibility and innovativeness), along with the basic social interaction variables (i.e., closeness and familiarity) and the major ICT inhibitors (i.e. risk and anxiety); with the aim to increase the understanding on the topic. As far as it is concerned, ‘Instagram checkout’ has never explored before. The results demonstrate that compatibility and performance expectancy exert the strongest positive effect on behavioral intention. Social influence and familiarity also influence positively m-users’ decisions to adopt ‘Instagram checkout’, whereas anxiety exerts a negative impact.

Taking time to identify expected products and waiting for the checkout in a retail store are common scenes we all encounter in our daily lives. The realization of automatic product recognition has great significance for both economic and social progress because it is more reliable than manual operation and time-saving. Product recognition via images is a challenging task in the field of computer vision. It receives increasing consideration due to the great application prospect, such as automatic checkout, stock tracking, planogram compliance, and visually impaired assistance. In recent years, deep learning enjoys a flourishing evolution with tremendous achievements in image classification and object detection. This article aims to present a comprehensive literature review of recent research on deep learning-based retail product recognition. More specifically, this paper reviews the key challenges of deep learning for retail product recognition and discusses potential techniques that can be helpful for the research of the topic. Next, we provide the details of public datasets which could be used for deep learning. Finally, we conclude the current progress and point new perspectives to the research of related fields.

With the continuous and rapid development of e-commerce, the requirements of logistics informatization are also increasing. At present, the barcode collection and identification device used in the operation of packages storage and checkout is generally based on ASIC chip, which is not fast enough. Therefore, this paper proposes a reconfigurable information acquisition and identification system, which is applied to the operation of package storage and delivery. This system uses FPGA + ARM architecture to realize the functions of identifying, storing and uploading the barcode information on the outer surface of the package to the host computer through UDP protocol. Because the parallel operation structure of FPGA is used to design the barcode image processing accelerator circuit, the data processing capacity of the soft core processor is reduced, and the recognition speed of the system is improved as a whole. The test shows that this system is faster and more accurate than the package barcode information recognition device based on ASIC technology.

Have you had a chance to check out the ITE Lands' End Storefront? Working with Lands' End as our corporate supplier, members can now go anytime to https://business.landsend. com/store/ite to order clothing and other merchandise branded with the ITE logo. Districts have also been invited to place their own logos on the ITE Storefront so that members can order clothing and merchandise with the District's logo as well. At checkout, just select the logo(s) that you want included on your merchandise.

ObjectiveThis project assesses how online vape shops (OVSs) verify buyer identification (ID) and the shipping methods used to send products within the USA.MethodologyIn January 2023, we conducted three online searches (eg, ‘best online vape shops’) from our office in Washington, District of Columbia, to identify popular OVSs. Two trained coders identified discrete features available within the site sections: ‘About Us’, ‘Shipping Policy’ and ‘Frequently Asked Questions’, or displayed within the site’s homepage. Coders recorded OVS listed locations, shipping discounts, shipping companies used and ID verification methods. Lastly, coders indicated if the site requested ID/age verification after adding an item to the shopping cart and initiating checkout procedures.ResultsWe identified 64 unique OVSs; 92.2% (n=59) offered shipping and 82.8% (n=53) shipped to US buyers; 76.6% (n=49) allowed visitors to type a birthday or choose the ‘21 or older’ option to access the site. Of the 59 sites shipping to buyers, 76.3% (n=45) offered free shipping, 21.9% (n=14) required login to purchase products, while most sites (n=45, 76.3%) allowed visitors to reach the checkout page without ID verification. The US Postal Service is the most commonly used shipping carrier (n=23), in violation of the Preventing All Cigarette Trafficking Act.ConclusionsMost OVSs rely on age self-certification, which underage youth can easily exploit to access these products. Findings warrant that the Food and Drug Administration, state and local policymakers explore additional actions regulating online tobacco sales to address the compliance issues our data elucidate. These include enhanced surveillance, compliance checks and stricter penalties.

With business process optimization, technological advancement, equipment capability enhancement, and other means, the Railway Passenger Service Department in China is consistently working to improve the efficiency and convenience of passenger entry and exit procedures at railway stations. Concerning passengers’ checkout, not only conventional identification approaches based on manual control, identification card, and magnetic thermal paper ticket are supported, but also a recent contactless identification process based on face recognition is applied in some stations. To further improve the contactless identification ability for checkout, an advanced contactless checkout process based on gait-augmented face recognition is innovatively put forward, in which a weakly-supervised body segmentation network named Dwsegnet and an improved GaitSet model are proposed. Through comparison with various models, the effectiveness of both Dwsegnet and the improved GaitSet is validated. Specifically, the contactless identification rate of gait-augmented face recognition is improved by 2.31% when compared to single-modal face recognition, which demonstrates the superiority of the proposed process.