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  1. Free, publicly-accessible full text available March 1, 2024
  2. Here, we examine the extension of smart retailing from the indoor confines of stores, outward to high streets. We explore how several technologies at the union of retail intelligence and smart city monitoring could coalesce into retail high streets that are both smart and sentient. We examine the new vantages that smart and sentient retail high streets provide on the customer journey, and how they could transform retailers’ sway over customer experience with new reach to the public spaces around shops. In doing so, we pursue a three-way consideration of these issues, examining the technology that underpins smart retailing, new advances in artificial intelligence and machine learning that beget a level of street-side sentience, and opportunities for retailers to map the knowledge that those technologies provide to individual customer journeys in outdoor settings. Our exploration of these issues takes form as a review of the literature and the introduction of our own research to prototype smart and sentient retail systems for high streets. The topic of enhancing retailers’ acuity on high streets has significant currency, as many high street stores have recently been struggling to sustain custom. However, the production and application of smart and sentient technologies at hyper-local resolution of the streetscape conjures some sobering considerations about shoppers’ and pedestrians’ rights to privacy in public. 
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    Free, publicly-accessible full text available December 1, 2023
  3. Abstract Background

    In this paper, we consider the applicability of the customer journey framework from retailing as a driver for urban informatics at individual scales within urban science. The customer journey considers shopper experiences in the context of shopping paths, retail service spaces, and touch-points that draw them into contact. Around this framework, retailers have developed sophisticated data science for observation, identification, and measurement of customers in the context of their shopping behavior. This knowledge supports broad data-driven understanding of customer experiences in physical spaces, economic spaces of decision and choice, persuasive spaces of advertising and branding, and inter-personal spaces of customer-staff interaction.


    We review the literature on pedestrian and high street retailing, and on urban informatics. We investigate whether the customer journey could be usefully repurposed for urban applications. Specifically, we explore the potential use of the customer journey framework for producing new insight into pedestrian behavior, where a sort of empirical hyperopia has long abounded because data are always in short supply.


    Our review addresses how the customer journey might be used as a structure for examining how urban walkers come into contact with the built environment, how people actively and passively sense and perceive ambient city life as they move, how pedestrians make sense of urban context, and how they use this knowledge to build cognition of city streetscapes. Each of these topics has relevance to walking studies specifically, but also to urban science more generally. We consider how retailing might reciprocally benefit from urban science perspectives, especially in extending the reach of retailers' insight beyond store walls, into the retail high streets from which they draw custom.


    We conclude that a broad set of theoretical frameworks, data collection schemes, and analytical methodologies that have advanced retail data science closer and closer to individual-level acumen might be usefully applied to accomplish the same in urban informatics. However, we caution that differences between retailers’ and urban scientists’ viewpoints on privacy presents potential controversy.

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  4. While tremendous advances in visual and auditory realism have been made for virtual and augmented reality (VR/AR), introducing a plausible sense of physicality into the virtual world remains challenging. Closing the gap between real-world physicality and immersive virtual experience requires a closed interaction loop: applying user-exerted physical forces to the virtual environment and generating haptic sensations back to the users. However, existing VR/AR solutions either completely ignore the force inputs from the users or rely on obtrusive sensing devices that compromise user experience. By identifying users' muscle activation patterns while engaging in VR/AR, we design a learning-based neural interface for natural and intuitive force inputs. Specifically, we show that lightweight electromyography sensors, resting non-invasively on users' forearm skin, inform and establish a robust understanding of their complex hand activities. Fuelled by a neural-network-based model, our interface can decode finger-wise forces in real-time with 3.3% mean error, and generalize to new users with little calibration. Through an interactive psychophysical study, we show that human perception of virtual objects' physical properties, such as stiffness, can be significantly enhanced by our interface. We further demonstrate that our interface enables ubiquitous control via finger tapping. Ultimately, we envision our findings to push forward research towards more realistic physicality in future VR/AR. 
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    Free, publicly-accessible full text available December 1, 2023
  5. Abstract

    In this review paper, we aim to make the case that a concept from retail analytics and marketing—thecustomer journey—can provide promising new frameworks and support for agent-based modeling, with a broad range of potential applications to high-resolution and high-fidelity simulation of dynamic phenomena on urban high streets. Although not the central focus of the review, we consider agent-based modeling of retail high streets against a backdrop of broader debate about downtown vitality and revitalization, amid a climate of economic challenges for brick-and-mortar retail. In particular, we consider how agent-based modeling, supported by insights from consideration of indoor shopping, can provide planning and decision support in outdoor high street settings. Our review considers abstractions of customers through conceptual modeling and customer typology, as well as abstractions of retailing as stationary and mobile. We examine high-level agency of shop choice and selection, as well as low-level agency centered on perception and cognition. Customer journeys are most often trips through geography; we therefore review path-planning, generation of foot traffic, wayfinding, steering, and locomotion. On busy high streets, journeys also manifest within crowd motifs; we thus review proximity, group dynamics, and sociality. Many customer journeys along retail high streets are dynamic, and customers will shift their journeys as they come into contact with experiences and service offerings. To address this, we specifically consider treatment of time and timing in agent-based models. We also examine sites for customer journeys, looking in particular at how agent-based models can provide support for the analysis of atmospherics, artifacts, and location-based services. Finally, we examine staff-side agency, considering store staff as potential agents outdoors; and we look at work to build agent-based models of fraud from customer journey analysis.

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  6. The aim of this work is to develop closer connectivity between real, lived human encounters in everyday life and geosimulation that might be tasked and designed to experiment with synthetic variations of those experiences. In particular, we propose that geosimulation can be used in close connection with virtual geographic environments and virtual reality environments to build human-in-the-loop interactivity between real people and geosimulation of the geographies that they experience. We introduce a novel scheme based on immersion and emission by socio-visual gaze to facilitate connectivity between human users and geosimulation. To examine the utility of the approach, we present a worked demonstration for examining road-crossing behavior in downtown settings for Brooklyn, NY. 
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  8. Montello, Daniel (Ed.)
  9. null (Ed.)