scholarly journals Workshop on Emerging Technology and Data Analytics for Behavioral Health

2018 ◽  
Vol 7 (6) ◽  
pp. e158 ◽  
Author(s):  
David Kotz ◽  
Sarah E Lord ◽  
A James O'Malley ◽  
Luke Stark ◽  
Lisa A Marsch
Keyword(s):  
Behavioral Health ◽  
Data Analytics ◽  
Emerging Technology

scholarly journals Workshop on Emerging Technology and Data Analytics for Behavioral Health (Preprint)

2017 ◽  
Author(s):  
David Kotz ◽  
Sarah E Lord ◽  
A James O'Malley ◽  
Luke Stark ◽  
Lisa A. Marsch
Keyword(s):  
Behavioral Health ◽  
Data Analytics ◽  
Health Behavior Change ◽  
Emerging Technology ◽  
Mobile Technologies ◽  
Dartmouth College ◽  
Future Research ◽  
Diverse Range ◽  
User Experience Design ◽  
Health Technologies

UNSTRUCTURED Wearable and portable digital devices can support self-monitoring for patients with chronic medical conditions, individuals seeking to reduce stress, and people seeking to modify health-related behaviors such as substance use or overeating. The resulting data may be used directly by a consumer, or shared with a clinician for treatment, a caregiver for assistance, or a health coach for support. The data can also be used by researchers to develop and evaluate just-in-time interventions that leverage mobile technology to help individuals manage their symptoms and behavior in real time and as needed. Such wearable systems have huge potential for promoting delivery of anywhere-anytime health care, improving public health, and enhancing the quality of life for many people. The Center for Technology and Behavioral Health at Dartmouth College, a P30 “Center of Excellence” supported by the National Institute on Drug Abuse at the National Institutes of Health, conducted a workshop in February 2017 on innovations in emerging technology, user-centered design, and data analytics for behavioral health, with presentations by a diverse range of experts in the field. The workshop focused on wearable and mobile technologies being used in clinical and research contexts, with an emphasis on applications in mental health, addiction, and health behavior change. In this paper, we summarize the workshop panels on mobile sensing, user experience design, statistics and machine learning, and privacy and security, and conclude with suggested research directions for this important and emerging field of applying digital approaches to behavioral health. Workshop insights yielded four key directions for future research: (1) a need for behavioral health researchers to work iteratively with experts in emerging technology and data analytics, (2) a need for research into optimal user-interface design for behavioral health technologies, (3) a need for privacy-oriented design from the beginning of a novel technology, and (4) the need to develop new analytical methods that can scale to thousands of individuals and billions of data points.

Bringing Scholarly Data Analytics Knowledge Using Emerging Technology Tools in Accounting into Classrooms: A Bibliometric Approach

2020 ◽  
Author(s):  
Qi Liu ◽  
Victoria Chiu ◽  
Brigitte W Muehlmann ◽  
Amelia Baldwin
Keyword(s):  
Information Systems ◽  
Intelligent Systems ◽  
Data Analytics ◽  
Accounting Information ◽  
Emerging Technology ◽  
Managerial Accounting ◽  
Accounting Information Systems ◽  
Accounting Research ◽  
Technology Tools ◽  
Scholarly Data

This study aims to help educators advance the integration of scholarly data analytics knowledge using emerging technology tools in accounting throughout the curriculum, thereby contributing to teaching for future-oriented practice. It provides an analysis of 215 peer-reviewed data analytics contributions including 16 classroom applications published from 2004 to 2018 in the six journals that have largely served as destinations of technology-related accounting research of all kinds and are commonly referred to as AIS journals, which are the Journal of Information Systems, International Journal of Accounting Information Systems, Journal of Emerging Technologies in Accounting, International Journal of Digital Accounting Research, AIS Educator Journal and Intelligent Systems in Accounting, Finance and Management. Accounting educators find detailed guidance on which peer-reviewed data analytics research contributions and tools are available to be integrated into financial and managerial accounting, auditing, accounting information systems, and tax courses.

Understanding the Value and Organizational Implications of Big Data Analytics: The Case of AUDI AG

2018 ◽  
Vol 8 (2) ◽  
pp. 126-138 ◽  
Author(s):  
Christian Dremel ◽  
Jochen Wulf ◽  
Annegret Maier ◽  
Walter Brenner
Keyword(s):  
Big Data ◽  
Automotive Industry ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Emerging Technology ◽  
Original Equipment Manufacturer ◽  
Equipment Manufacturer ◽  
Strong Interest

“Understanding the value and organizational implications of big data analytics: the case of AUDI AG” presents the case of AUDI AG and its attempts to implement big data analytics in its organization. The case highlights the situation of an original equipment manufacturer (OEM) in the automotive industry and the potentials and challenges the emerging technology big data analytics may entail for such organizations. The case tries to help students to grasp the technical characteristics, the value, and organizational implications of big data analytics as well as the distinct types of analytics services. The case is presented through the eyes of Hortensie, an aspiring manager at AUDI, who gained strong interest in the phenomenon of big data analytics and received the task to position it within AUDI. To ramp up the topic big data analytics, AUDI is engaging with industry and design experts as well as an external consultancy ITConsult.

People analytics and the rise of HR: how data, analytics and emerging technology can transform human resources (HR) into a profit center

2019 ◽  
Vol 18 (2) ◽  
pp. 42-46 ◽  
Author(s):  
Michael DiClaudio
Keyword(s):  
Data Analytics ◽  
Predictive Analytics ◽  
Emerging Technology ◽  
Customer Relationship ◽  
High Turnover ◽  
Content Type ◽  
Profit Center ◽  
Cloud Data ◽  
Strategic Value ◽  
Hr Function

Purpose Employee and workforce insights are the greatest competitive advantage for organizations dealing with the disruption and uncertainty driving dramatic changes in today’s workplace. Embedded in this is the growing expectation of the human resource (HR) function to understand how workforce analytics informs the business and fuels success. This paper aims to explore how the HR function can achieve this. Design/methodology/approach The evolution of the “Future of HR” and how it is moving from “descriptive and diagnostic” to “prescriptive and predictive.” Findings According to KPMG’s 2019 Future of HR survey: 37 per cent of respondents feel “very confident” about HR’s actual ability to transform and move them forward via key capabilities such as analytics and artificial intelligence (AI). Over the next year or two, 60 per cent say they plan to invest in predictive analytics. Among those who have invested in AI to date, 88 per cent call the investment worthwhile, with analytics listed as a main priority (33 per cent). Despite data’s remarkable ability to deliver news insights and enhance decision-making, 20 per cent of HR believe analytics will be a primary HR initiative for them over the next one to two years, and only 12 per cent cite analytics as a top management concern. Research limitations/implications Taking a page from meeting customer needs, innovative technologies such as AI and the cloud, data analytics can give an organization the potential to gather infinitely greater amounts of information about customers. Practical implications Today’s workforce analytics focuses mostly on what happened and why. For instance, you might have tools for identifying areas of high turnover and diagnosing the reasons. But thanks to advancements in technology and data analytics capabilities, HR is better-positioned to be the predictive engine required for the organization’s success. Social implications There has never been a better time for HR to create greater strategic value, as the potential for meaningful workforce insights and analytics comes within reach. Even advancements in cloud-based systems for human capital management are coming packaged with analytics and visualization capabilities, enabling HR leaders to integrate people data with other data sources, such as customer relationship management, for a full view of the business. Originality/value This paper will be of value to HR leaders and practitioners who wish to use predictive analytics and emerging technology to drive performance improvement and gain the insights about their workforces.

Data Analytics for Strategic Management

2017 ◽  
pp. 810-822
Author(s):  
Lesley S. J. Farmer
Keyword(s):  
Strategic Management ◽  
Data Analytics ◽  
Management Practices ◽  
Emerging Technology ◽  
Data Driven ◽  
Evidence Based ◽  
Current Management ◽  
The Right ◽  
Impact Data ◽  
Analyze Data

To direct and maintain smooth operations in coordination with internal and external sectors, strategic managers need to collect and analyze data about those operations and stakeholders so they can improve current management practices and determine new management direction. Particularly in today's data-driven society where evidence-based practice is expected, numbers and other evidence abound. However, data by itself is not very useful or even informative. Managers need to strategically conduct data analytics, that is the process of knowing the right questions to ask, determining the relevant data to collect, choosing the appropriate instruments to collect those data, analyzing that data, recommending appropriate actions, implementing them, and evaluating the implementation. This chapter also emerging technology issues and tools that impact data analytics.

What's “Rural” About Rural Behavioral Health?

2004 ◽  
Vol 49 (5) ◽  
pp. 633-635
Author(s):  
Gary B. Melton
Keyword(s):  
Behavioral Health

Integrated behavioral health in primary care: Step-by-step guidance for assessment and intervention.

2009 ◽  
Author(s):  
Christopher L. Hunter ◽  
Jeffrey L. Goodie ◽  
Mark S. Oordt ◽  
Anne C. Dobmeyer
Keyword(s):  
Primary Care ◽  
Behavioral Health ◽  
Integrated Behavioral Health
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