Field evaluation of a mobile app for assisting blind and visually impaired travelers to find bus stops

Purpose: It is reported that there can be considerable gaps due to GPS inaccuracy and mapping errors if blind and visually impaired (BVI) travelers rely on digital maps to go to their desired bus stops. We evaluated the ability of a mobile app, All_Aboard, to guide BVI travelers precisely to the bus-stops. Methods: The All_Aboard app detected bus-stop signs in real-time via smartphone camera using a neural network model, and provided distance coded audio feedback to help localize the detected sign. BVI individuals used the All_Aboard and Google Maps app to localize 10 bus-stop locations in Boston downtown and another 10 in a sub-urban area. For each bus stop, the subjects used the apps to navigate as close as possible to the physical bus-stop sign, starting from 30 to 50 meters away. The outcome measures were success rate and gap distance between the app-indicated location and the actual physical location of the bus stop. Results: The study was conducted with 24 legally blind participants (mean age [SD]: 51[14] years; 11 (46%) Female). The success rate of the All_Aboard app (91%) was significantly higher than the Google Maps (52%, p<0.001). The gap distance when using the All_Aboard app was significantly lower (mean [95%CI]: 1.8 [1.2-2.3] meters) compared to the Google Maps (7 [6.5-7.5] meters; p<0.001). Conclusion: The All_Aboard app localizes bus stops more accurately and reliably than GPS-based smartphone navigation options in real-world environments

An Inquiry into Supply Chain Strategy Implications of the Sharing Economy for Last Mile Logistics

As the prevalence of e-commerce and subsequent importance of effective and efficient omnichannel logistics strategies continues to rise, retail firms are exploring the viability of sourcing logistics capabilities from the sharing economy. Questions arise such as, “how can crowdbased logistics solutions such as crowdsourced logistics (CSL), crowdshipping, and pickup point networks (PPN) be leveraged to increase performance?” In this dissertation, empirical and analytical research is conducted that increases understanding of how firms can leverage the sharing economy to increase logistics and supply chain performance. Essay 1 explores crowdsourced logistics (CSL) by employing a stochastic discrete event simulation set in New York City in which a retail firm sources drivers from the crowd to perform same day deliveries under dynamic market conditions. Essay 2 employs a design science paradigm to develop a typology of crowdbased logistics strategies using two qualitative methodologies: web content analysis and Delphi surveys. A service-dominant logic theoretical perspective guides this essay and explains how firms co-create value with the crowd and consumer markets while presenting a generic design for integrating crowdbased models into logistics strategy. In Essay 3, a crowdsourced logistics strategy for home delivery is modeled in an empirically grounded simulation optimization to explore the logistics cost and responsiveness implications of sharing economy solutions on omnichannel fulfillment strategies

Iterative Design and Prototyping of Computer Vision Mediated Remote Sighted Assistance

Remote sighted assistance (RSA) is an emerging navigational aid for people with visual impairments (PVI). Using scenario-based design to illustrate our ideas, we developed a prototype showcasing potential applications for computer vision to support RSA interactions. We reviewed the prototype demonstrating real-world navigation scenarios with an RSA expert, and then iteratively refined the prototype based on feedback. We reviewed the refined prototype with 12 RSA professionals to evaluate the desirability and feasibility of the prototyped computer vision concepts. The RSA expert and professionals were engaged by, and reacted insightfully and constructively to the proposed design ideas. We discuss what we learned about key resources, goals, and challenges of the RSA prosthetic practice through our iterative prototype review, as well as implications for the design of RSA systems and the integration of computer vision technologies into RSA

Sharing Economy Last Mile Delivery: Three Essays Addressing Operational Challenges, Customer Expectations, and Supply Uncertainty

Last mile delivery has become a critical competitive dimension facing retail supply chains. At the same time, the emergence of sharing economy platforms has introduced unique operational challenges and benefits that enable and inhibit retailers’ last mile delivery goals. This dissertation investigates key challenges faced by crowdshipping platforms used in last mile delivery related to crowdsourced delivery drivers, driver-customer interaction, and customer expectations. We investigate the research questions of this dissertation through a multi-method design approach, complementing a rich archival dataset comprised of several million orders retrieved from a Fortune 100 retail crowdshipping platform, with scenario-based experiments. Specifically, the first study analyzes the impact of delivery task remuneration and operational characteristics that impact drivers’ pre-task, task, and post-task behaviors. We found that monetary incentives are not the sole factor influencing drivers’ behaviors. Drivers also consider the operational characteristics of the task when accepting, performing, and evaluating a delivery task. The second study examines a driver’s learning experience relative to a delivery task and the context where it takes place. Results show the positive impact of driver familiarity on delivery time performance, and that learning enhances the positive effect. Finally, the third study focuses on how delivery performance shape customers’ experience and future engagement with the retailer, examining important contingency factors in these relationships. Findings support the notion that consumers time-related expectations on the last mile delivery service influence their perceptions of the delivery performance, and their repurchase behaviors. Overall, this dissertation provides new insights in this emerging field that advance theory and practice

Sharing Economy Last Mile Delivery: Three Essays Addressing Operational Challenges, Customer Expectations, and Supply Uncertainty

Last mile delivery has become a critical competitive dimension facing retail supply chains. At the same time, the emergence of sharing economy platforms has introduced unique operational challenges and benefits that enable and inhibit retailers’ last mile delivery goals. This dissertation investigates key challenges faced by crowdshipping platforms used in last mile delivery related to crowdsourced delivery drivers, driver-customer interaction, and customer expectations. We investigate the research questions of this dissertation through a multi-method design approach, complementing a rich archival dataset comprised of several million orders retrieved from a Fortune 100 retail crowdshipping platform, with scenario-based experiments. Specifically, the first study analyzes the impact of delivery task remuneration and operational characteristics that impact drivers’ pre-task, task, and post-task behaviors. We found that monetary incentives are not the sole factor influencing drivers’ behaviors. Drivers also consider the operational characteristics of the task when accepting, performing, and evaluating a delivery task. The second study examines a driver’s learning experience relative to a delivery task and the context where it takes place. Results show the positive impact of driver familiarity on delivery time performance, and that learning enhances the positive effect. Finally, the third study focuses on how delivery performance shape customers’ experience and future engagement with the retailer, examining important contingency factors in these relationships. Findings support the notion that consumers time-related expectations on the last mile delivery service influence their perceptions of the delivery performance, and their repurchase behaviors. Overall, this dissertation provides new insights in this emerging field that advance theory and practice

The platform effect: How Amazon changed work in logistics in Germany, the United States and the United Kingdom

While the effects of the platform economy on work are mainly studied through the lens of gig or cloud workers, many more employees are likely to be affected in non-platform firms or sectors. We discuss the mechanisms of platform economy’s impact on the employment relationships and indirect effect on employment trends. Platform firms enter the service economy with business models that put existing service providers under pressure and advance a platform model of employment relationship. However, their transformative force is limited by three factors: employment regulations, access to welfare provisions and the employment relations at legacy firms. We examine the case of Amazon logistics in the US, Germany and the UK and find that the employment contract, as a legal institution, prevents the dissemination of independent contracting as the preferred employment model. Moreover, the welfare state has a paradoxical effect on platform work: universal welfare and liberal employment law facilitate the rise of precarious work

Delivering Goods Using a Baby Pram : The Sustainability of Last-Mile Logistics Business Models

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Autonomous ground vehicles in urban last-mile delivery : an exploration of the implementation feasibility and consumer’s acceptance

E-Commerce has rapidly changed the urban last-mile delivery in recent years, and Courier-, Express- and Parcel (CEP) companies are challenged by the increasing demand. Service robotics with autonomous vehicles are subject to be the catalyst for transforming the industry. Considering the infancy and lack of research on the subject, the purpose of this study is to explore the concept of autonomous ground vehicles (AGVs) in urban last-mile delivery from two perspectives. First, data about the industry and insights from the technology provider summarize the status quo of recent developments and implementation barriers with the help of expert interviews. The findings show obstacles in the technological maturity and regulatory framework. Moreover, although only road-AGVs (rAGVs) will significantly change the industry, sidewalk-AGVs (sAGVs) act as a proof of concept as the implementation is more feasible. In addition, they create new premium services for the consumers. Second, an attempt to determine the consumer’s acceptance of sAGVs, using the combination of the technology acceptance model and the technology readiness index, is made with an online survey. The proposed research model is analysed by means of simple regression analysis, and all hypotheses are supported. The majority of the respondents have a positive attitude towards the concept of sAGVs for delivery and consider using it when the safety of their delivery goods is guaranteed. This dissertation enriches the literature on human-robot acceptance as well as the management of CEP-companies to increase the engagement in the implementation of sidewalk-AGVs to increase service innovation for consumers.O comércio electrónico mudou rapidamente a entrega urbana de bens ao consumidor, e as empresas de Correio Expresso Urgente são desafiadas pela procura crescente. Os serviços robóticos com veículos autónomos serão provavelmente o catalisador da transformação desta indústria. Considerando a falta e o estágio inicial de investigação, este estudo explora o conceito de veículos autónomos terrestres (AGVs) na entrega urbana de bens ao consumidor considerando duas perspetivas. Uma primeira será a de recolher dados sobre a indústria e insights de fornecedores da tecnologia, sumarizando os mais recentes desenvolvimentos e as barreiras à implementação, com a ajuda de entrevistas a especialistas. Os resultados revelam obstáculos na maturidade tecnológica e enquadramento regulamentar. Adicionalmente, embora apenas os AGVs rodoviários (rAGVs) virão a alterar significativamente a indústria, os AGVs de passeio (sAGVs) atuam como prova de conceito, dada a sua implementação viável. Em segundo lugar, a aceitação de sAGVs por parte do consumidor é determinada através da combinação de modelos de aceitação tecnológica e do índex de prontidão de tecnologia, via questionário online. O modelo de investigação proposto é testado por meio de análise de regressão simples, e todas as hipóteses são suportadas. A maioria dos participantes tem uma atitude positiva em relação aos sAGVs para entrega, e considera usá-los se a segurança dos seus bens for garantida. Esta dissertação enriquece a literatura sobre aceitação humana-robot, bem como a gestão de empresas de Correio Expresso Urgente, aumentando o envolvimento na implementação de sAGVs e fomentando a inovação em serviços para o consumidor

Networking Transportation

Networking Transportation looks at how the digital revolution is changing Greater Philadelphia's transportation system. It recognizes several key digital transportation technologies: Artificial Intelligence, Big Data, connected and automated vehicles, digital mapping, Intelligent Transportation Systems, the Internet of Things, smart cities, real-time information, transportation network companies (TNCs), unmanned aerial systems, and virtual communications. It focuses particularly on key issues surrounding TNCs. It identifies TNCs currently operating in Greater Philadelphia and reviews some of the more innovative services around the world. It presents four alternative future scenarios for their growth: Filling a Niche, A Tale of Two Regions, TNCs Take Off, and Moore Growth. It then creates a future vision for an integrated, multimodal transportation network and identifies infrastructure needs, institutional reforms, and regulatory recommendations intended to help bring about this vision