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Many restaurants have recently implemented self-order technologies across both online and offline channels. Online technology, through websites and mobile apps, allows customers to order and pay before coming to the store; offline technology, such as self-service kiosks, allows store customers to place orders without interacting with a human employee. In this paper, we develop a stylized theoretical model to study the impact of self-order technologies on customer demand, employment levels, and restaurant profits. Our main results follow. First, customers using self-order technologies experience reduced waiting cost and increased demand, and moreover, these benefits may even carry over to customers who do not use these technologies. Second, although public opinion suggests that self-order technologies facilitate job cuts, we find instead that some firms should increase employment levels, and, paradoxically, this recommendation holds for firms with high labor costs. Finally, we find that firms should implement online (offline) self-order technology when customers have high (low) wait sensitivity. The supplementary appendix is available at https://doi.org/10.1287/mnsc.2017.2787 . This paper was accepted by Serguei Netessine, operations management.

To improve the accuracy of material identification under low contrast conditions, this paper proposes an improved YOLOv4-tiny target detection method based on an adaptive self-order piecewise enhancement and multiscale feature optimization. The model first constructs an adaptive self-rank piecewise enhancement algorithm to enhance low-contrast images and then considers the fast detection ability of the YOLOv4-tiny network. To make the detection network have a higher accuracy, this paper adds an SE channel attention mechanism and an SPP module to this lightweight backbone network to increase the receptive field of the model and enrich the expression ability of the feature map. The network can pay more attention to salient information, suppress edge information, and effectively improve the training accuracy of the model. At the same time, to better fuse the features of different scales, the FPN multiscale feature fusion structure is redesigned to strengthen the fusion of semantic information at all levels of the network, enhance the ability of network feature extraction, and improve the overall detection accuracy of the model. The experimental results show that compared with the mainstream network framework, the improved YOLOv4-tiny network in this paper effectively improves the running speed and target detection accuracy of the model, and its mAP index reaches 98.85%, achieving better detection results.

Makes the case for forming new international partnerships and revitalizing instruments of cooperation to address global challenges that post-WWII multilateral security systems cannot. Establishes a new conceptual foundation for international security: 'responsible sovereignty, ' which entails obligations and duties and attitudinal changes toward other states as well one's own.

Becoming Humanargues that human identity was articulated and extended across a wide range of textual, visual, and artifactual assemblages from the twelfth to the fifteenth centuries. J. Allan Mitchell shows how the formation of the child expresses a manifold and mutable style of being. To be human is to learn to dwell among a welter of things. A searching and provocative historical inquiry into human becoming, the book presents a set of idiosyncratic essays on embryology and infancy, play and games, and manners, meals, and other messes. While it makes significant contributions to medieval scholarship on the body, family, and material culture,Becoming Humantheorizes anew what might be called a medieval ecological imaginary. Mitchell examines a broad array of phenomenal objects-including medical diagrams, toy knights, tableware, conduct texts, dream visions, and scientific instruments-and in the process reanimates distinctly medieval ontologies. In addressing the emergence of the human in the later Middle Ages, Mitchell identifies areas where humanity remains at risk. In illuminating the past, he shines fresh light on our present.

By examining environmental change through the lens of conflicting social agendas, Andrew Hurley uncovers the historical roots of environmental inequality in contemporary urban America. Hurley's study focuses on the steel mill community of Gary, Indiana, a city that was sacrificed, like a thousand other American places, to industrial priorities in the decades following World War II. Although this period witnessed the emergence of a powerful environmental crusade and a resilient quest for equality and social justice among blue-collar workers and African Americans, such efforts often conflicted with the needs of industry. To secure their own interests, manufacturers and affluent white suburbanites exploited divisions of race and class, and the poor frequently found themselves trapped in deteriorating neighborhoods and exposed to dangerous levels of industrial pollution. In telling the story of Gary, Hurley reveals liberal capitalism's difficulties in reconciling concerns about social justice and quality of life with the imperatives of economic growth. He also shows that the power to mold the urban landscape was intertwined with the ability to govern social relations. |Features the pathbreaking work of Mark Catesby, the British naturalist and illustrator who founded natural history and bird art in America, preceding Audubon by nearly a century.