The Disruptive Impact of Emerging Technology

2015 ◽  
pp. 233-256 ◽  
Author(s):  
Gordon J. Murray
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Disruptive Innovation ◽  
Emerging Technology ◽  
Decision Making Processes ◽  
Data Journalism ◽  
Day To Day Operations ◽  
Map Data ◽  
Access Data ◽  
Wireless Mobile

In this chapter, context for understanding the phenomenon of “big data” and disruptive innovation is introduced relative to current changes affecting the future of the journalism industry. Perspective is provided on market forces and emerging technologies that now shape the demand for data journalism. Current best practices and strategies to analyze, scrape, personalize, visualize and map data are presented. Trends and resources to access data and effectively analyze information are outlined for journalists to use when researching and reporting online. Three contemporary case studies explore the day-to-day operations and decision-making processes of media organizations struggling to remain profitable; adapt to changing consumer demands and try to serve a new demographic that is increasingly global, wireless, mobile and socially networked.

The Disruptive Impact of Emerging Technology

Big Data ◽  
2016 ◽  
pp. 2226-2248
Author(s):  
Gordon J. Murray
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Disruptive Innovation ◽  
Emerging Technology ◽  
Decision Making Processes ◽  
Data Journalism ◽  
Day To Day Operations ◽  
Map Data ◽  
Access Data ◽  
Wireless Mobile

In this chapter, context for understanding the phenomenon of “big data” and disruptive innovation is introduced relative to current changes affecting the future of the journalism industry. Perspective is provided on market forces and emerging technologies that now shape the demand for data journalism. Current best practices and strategies to analyze, scrape, personalize, visualize and map data are presented. Trends and resources to access data and effectively analyze information are outlined for journalists to use when researching and reporting online. Three contemporary case studies explore the day-to-day operations and decision-making processes of media organizations struggling to remain profitable; adapt to changing consumer demands and try to serve a new demographic that is increasingly global, wireless, mobile and socially networked.

Evolution of e-participation in Greek local government

2021 ◽  
pp. 1-15
Author(s):  
Constantina Costopoulou ◽  
Maria Ntaliani ◽  
Filotheos Ntalianis
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Local Government ◽  
Local Governments ◽  
Local Community ◽  
New Technologies ◽  
Mobile Apps ◽  
Digital Technologies ◽  
Decision Making Processes ◽  
The Impact

Local governments are increasingly developing electronic participation initiatives, expecting citizen involvement in local community affairs. Our objective was to assess e-participation and the extent of its change in local government in Greece. Using content analysis for 325 Greek municipal websites, we assessed e-participation status in 2017 and 2018 and examined the impact of change between these years. The assessment regards two consecutive years since the adoption of digital technologies by municipalities has been rapid. The main findings show that Greek local governments have made significant small- to medium-scale changes, in order to engage citizens and local societies electronically. We conclude that the integration of advanced digital technologies in municipalities remains underdeveloped. We propose that Greek municipalities need to consider incorporating new technologies, such as mobile apps, social media and big data, as well as e-decision making processes, in order to eliminate those obstacles that hinder citizen engagement in local government. Moreover, the COVID-19 outbreak has highlighted the need for enhancing e-participation and policymakers’ coordination through advanced digital technologies.

Conquery: an Open Source Application to analyze High Content Healthcare Data (Preprint)

2021 ◽  
Author(s):  
Fabian Kovacs ◽  
Max Thonagel ◽  
Marion Ludwig ◽  
Alexander Albrecht ◽  
Manuel Hegner ◽  
...  
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Medical Records ◽  
Healthcare Sector ◽  
Study Cohort ◽  
Decision Making Processes ◽  
Analytical Approaches

BACKGROUND Big data in healthcare must be exploited to achieve a substantial increase in efficiency and competitiveness. Especially the analysis of patient-related data possesses huge potential to improve decision-making processes. However, most analytical approaches used today are highly time- and resource-consuming. OBJECTIVE The presented software solution Conquery is an open-source software tool providing advanced, but intuitive data analysis without the need for specialized statistical training. Conquery aims to simplify big data analysis for novice database users in the medical sector. METHODS Conquery is a document-oriented distributed timeseries database and analysis platform. Its main application is the analysis of per-person medical records by non-technical medical professionals. Complex analyses are realized in the Conquery frontend by dragging tree nodes into the query editor. Queries are evaluated by a bespoke distributed query-engine for medical records in a column-oriented fashion. We present a custom compression scheme to facilitate low response times that uses online calculated as well as precomputed metadata and data statistics. RESULTS Conquery allows for easy navigation through the hierarchy and enables complex study cohort construction whilst reducing the demand on time and resources. The UI of Conquery and a query output is exemplified by the construction of a relevant clinical cohort. CONCLUSIONS Conquery is an efficient and intuitive open-source software for performant and secure data analysis and aims at supporting decision-making processes in the healthcare sector.

Unpacking Big Data in Education. A Research Framework

2017 ◽  
Vol 8 (2) ◽  
pp. 123-137
Author(s):  
Rosanna De Rosa ◽  
Biagio Aragona
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Use ◽  
Digital Tools ◽  
Policy Cycle ◽  
Core Element ◽  
Technological Revolution ◽  
Research Framework ◽  
Scarce Resources ◽  
Decision Making Processes

Abstract The use of big data represents a valuable way to inspire decision-making in a time of scarce resources. The technological revolution is in fact enabling governments to use a great variety of digital tools and data to manage all phases of the policy cycle process, becoming a core element for e-governance applications and techniques. However, research is seemingly not yet aligned yet with the hybrid environment that both public policies and politics are moving in, while the actors (old and new) and the decision-making processes themselves, in their searching for automation and objectivity, risk being overshadowed. Taking the case of Higher Education, this article proposes a research framework for big-data use to prompt the reflection on the power of “evidence” in decision making; to question and contextualize such evidences in a multimodal and integrated scenario, and to understand the challenges that data will pose to education both in terms of unforeseen and hidden effects.

scholarly journals Human-related capabilities in big data analytics: a taxonomy of human factors with impact on firm performance

2021 ◽  
Author(s):  
Philipp Korherr ◽  
Dominik Kanbach
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Scientific Basis ◽  
Critical Factors ◽  
Organizational Capability ◽  
First Order ◽  
Management Capability ◽  
Decision Making Processes

AbstractThis study intends to provide scholars and practitioners with an understanding of human resource challenges in the context of Big Data Analytics (BDA). This paper provides a holistic framework of human-related capabilities that organizations must consider when implementing BDA to facilitate decision-making. For this purpose, the authors conducted a systematic literature review adapted from Tranfield et al. (BJM 14:207–222, 2003) to identify relevant studies. The 75 publications reviewed provided the sample for an inductive, and systematic data evaluation following the well-known and accepted approach introduced by Gioia et al. (ORM 16:15–31, 2012). The comprehensive review uncovered 33 first-order concepts linked to human-related capabilities, which were distilled into 15 s-order themes and then merged into five aggregated dimensions: Personnel Capability, Management Capability, Organizational Capability, Culture and Governance Capability, and Strategy and Planning Capability. The study is, to the best of the authors’ knowledge, the first to categorize all relevant human-related capabilities for successful BDA application. As such, it not only provides the scientific basis for further research, but also serves as a useful overview of the critical factors for BDA use in decision-making processes.

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