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Functional Structure and Approximation in Econometrics
Type: Book
ISBN: 978-0-44450-861-4

Book part
Publication date: 20 September 2018

Arwen H. DeCostanza, Katherine R. Gamble, Armando X. Estrada and Kara L. Orvis

Unobtrusive measurement methodologies are critical to implementing intelligent tutoring systems (ITS) for teams. Such methodologies allow for continuous measurement of team states…

Abstract

Unobtrusive measurement methodologies are critical to implementing intelligent tutoring systems (ITS) for teams. Such methodologies allow for continuous measurement of team states and processes while avoiding disruption of mission or training performance, and do not rely on post hoc feedback (including for the aggregation of data into measures or to develop insights from these real-time metrics). This chapter summarizes advances in unobtrusive measurement developed within Army research programs to illustrate the variety and potential that unobtrusive measurement approaches can provide for building ITS for teams. Challenges regarding the real-time aggregation of data and applications to current and future ITS for teams are also discussed.

Book part
Publication date: 7 August 2019

Cristina Alaimo and Jannis Kallinikos

Social media stage online patterns of social interaction that differ remarkably from ordinary forms of acting, talking and relating. To unravel these differences, we review the…

Abstract

Social media stage online patterns of social interaction that differ remarkably from ordinary forms of acting, talking and relating. To unravel these differences, we review the literature on micro-sociology and social psychology and derive a shorthand version of socially-embedded forms of interaction. We use that version as a yardstick for reconstructing and assessing the patterns of sociality social media promote. Our analysis shows that social media platforms stage highly stylized forms of social interaction such as liking, following, tagging, etc. that essentially serve the purpose of generating a calculable and machine-readable data footprint out of user platform participation. This online stylization of social interaction and the data it procures are, however, only the first steps of what we call the infrastructuring of social media. Social media use the data footprint that results from the stylization of social interaction to derive larger (and commercially relevant) social entities such as audiences, networks and groups that are constantly fed back to individuals and groups of users as personalized recommendations of one form or another. Social media infrastructure sociality as they provide the backstage operations and technological facilities out of which new habits and modes of social relatedness emerge and diffuse across the social fabric.

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A Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education
Type: Book
ISBN: 978-1-78973-900-8

Book part
Publication date: 12 December 2017

Libby Bishop and Daniel Gray

The focus of this chapter is the intersection of social media, publication, data sharing, and research ethics. By now there is an extensive literature on the use of social media…

Abstract

The focus of this chapter is the intersection of social media, publication, data sharing, and research ethics. By now there is an extensive literature on the use of social media in research. There is also excellent work on challenges of postpublication sharing of social media, primarily focused on legal restrictions, technical infrastructure, and documentation. This chapter attempts to build upon and extend this work by using cases to deepen the analysis of ethical issues arising from publishing and sharing social media data. Publishing will refer to the presentation of data extracts, aggregations, or summaries, while sharing refers to the practice of making the underlying data available postpublication for others to use. It will look at the ethical questions that arise both for researchers (or others) sharing data, and those who are using data that has been made available by others, emphasizing the inherently relational nature of data sharing. The ethical challenges researchers face when considering sharing user-generated content collected from social media platforms are the focus of the cases. The chapter begins by summarizing the general principles of research ethics, then identifies the specific ethical challenges from sharing social media data and positions these challenges in the context of these general principles. These challenges are then analyzed in more detail with cases from research projects that drew upon several different genres of social media. The chapter concludes with some recommendations for practical guidance and considers the future of ethical practice in sharing social media data.

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The Ethics of Online Research
Type: Book
ISBN: 978-1-78714-486-6

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Book part
Publication date: 1 March 2021

John P. Koeplin and Pascal Lélé

Integrating interdisciplinary studies with Human Capital Management Accounting (HCMA) refers to the dynamics of organized interdisciplinary action that are transversal or…

Abstract

Integrating interdisciplinary studies with Human Capital Management Accounting (HCMA) refers to the dynamics of organized interdisciplinary action that are transversal or cross-cutting. This approach requires the mastery of a certain number of technical skills and disciplines, as well as the capacity to use them in a process to solve problems of financial performance. This is accomplished through the specific interaction tasks that are performed by each management function and operational unit, which act in real time with others, in the same direction as an organizational team, using a selected risk appetite threshold base.

Putting business fields side by side, (i.e., business disciplines silos, as is normally the case in MBA programs), is not enough to create the transversal interaction dynamic needed for firms to achieve expected financial performance goals. As a result, few graduates today have the cross-cutting or vertical skills required to act, in real time, from their workstation in accordance with the pyramid shape of the organization chart in order to create value.

This chapter presents the results of the interface established by a faculty member in the Accounting Department of the University of San Francisco with a “seasoned leader in the FinTech industry.” It proposes a single portal for employers and HRMs to which the continuing education services of professional training associations, executive education departments of colleges, and MBA schools and universities, can connect to issue the HCMA certificate supplementing their training offerings focused on “Leadership Development”.

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Recent Developments in Asian Economics International Symposia in Economic Theory and Econometrics
Type: Book
ISBN: 978-1-83867-359-8

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A Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education
Type: Book
ISBN: 978-1-78973-900-8

Book part
Publication date: 26 October 2017

Virginia M. Miori, Kathleen Campbell Garwood and Catherine Cardamone

This is the second in a series of papers focused on alcohol and substance abuse rehabilitation centers. Centers face the ongoing challenge of validating outcomes to meet the…

Abstract

This is the second in a series of papers focused on alcohol and substance abuse rehabilitation centers. Centers face the ongoing challenge of validating outcomes to meet the burden of evidence for insurance companies. In the first paper, data mining was used to establish baseline patterns in treatment success rates, for the Futures: Palm Beach Rehabilitation Center, that have a direct impact on a client’s ability to receive insurance coverage for treatment programs. In this paper, we examine 2016 outcomes and report on facility efficacy, alumni progression and sobriety, and forecast treatment success rates (short and long term) in support of client insurability. Data collection has been standardized and includes admissions data, electronic medical records data, satisfaction survey data, post-discharge survey data, Centers for Disease Control (CDC) data, and demographic data. Clustering, partitioning, ANOVA, stepwise regression and stepwise Logistic regression are applied to the data to determine statistically significant drivers of treatment success.

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78743-069-3

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Handbook of Transport Modelling
Type: Book
ISBN: 978-0-08-045376-7

1 – 10 of over 2000