The Internet of Everywhere (IoE): Places, People, and Things
Permanent URI for this collectionhttps://hdl.handle.net/10125/107525
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Item type: Item , Biometric Affordances and Ethical Dilemmas: Considerations for a Better Workplace(2024-01-03) Killoran, Jayson; Manseau, JasminBiometric technologies are at the forefront of organizational innovation, surveillance, and control. In many instances, the use of physiological and behavioral biometrics are enhancing individual and organizational performance, but there is an increasing risk of privacy invasion and the unethical use of biometrics. Moreover, biometrics have received relatively scant theoretical attention. In this paper, we draw from the theory of affordances to identify and delineate seven affordances of biometric technologies, categorized into inhibiting and augmenting biometric affordances. We also connect each biometric affordance with the potential for ethical dilemmas to arise. This paper contributes a theoretical framework which we hope will guide future research, and we offer implications for practitioners to mindfully integrate biometric technologies without causing harm to human wellbeing.Item type: Item , Demand Prediction by Incorporating Internet-of-Things Data: A Case of Automobile Repair and Maintenance Service(2024-01-03) Zhang, Jieyi; Yang, Cenying; Feng, YihaoWhile anecdotal evidence highlights the value of Internet-of-Things (IoT) data for business operations, rigorous empirical validation is still limited. The key challenge lies in integrating IoT analytics into business evaluation. To address the issues, we focus on the automotive industry and study the value of telematics data, an important IoT application in this domain, in terms of predicting maintenance, repair, and operations (MRO) service demands. Our approach involves building a prediction system with users’ driving behavior, MRO service records, and environmental data (weather and traffic). We show a substantial improvement in prediction performance upon incorporating user behavior information derived from IoT data. Specifically, we find that hard acceleration, hard braking, and speeding rank the third, fifth, and sixth, respectively, in terms of their contribution to the MRO prediction. Our results shed light on the design of product-service systems (PSS), an emerging trend to integrate product offerings with service offerings.Item type: Item , Introduction to the Minitrack on The Internet of Everywhere (IoE): Places, People, and Things(2024-01-03) Beer, Jeremy; Schau, Hope; Kietzmann, Jan