Big Data and Management
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TLDR
The authors reflect on management of big data by organizations and comment on service level agreements (SLA) which define the nature and quality of information technology services and mention big data-sharing agreements tend to be poorly structured and informal.Abstract:
The authors reflect on management of big data by organizations. They comment on service level agreements (SLA) which define the nature and quality of information technology services and mention big data-sharing agreements tend to be poorly structured and informal. They reflect on the methodologies of analyzing big data and state it is easy to get false correlations when using typical statistical tools in analyzing big data. They talk about the use of big data in management and behavior research.read more
Citations
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An organizational digital footprint for interruption management: a data-driven approach
TL;DR: In this paper , the authors provide a demonstration of using trace data from information and communications technology (ICT)-systems and machine learning to identify interrupting situations, which can be used to identify situations across which the level of interruptions differs.
Proceedings ArticleDOI
Digitalization of Knowledge Development in the Media Industry
TL;DR: In this article , a case study of one of Norway's larger publishing houses, with ownership in several newspapers and online media platforms, was conducted during 2021 and is based on 10 different interviews with newspaper editors, journalists, commercial managers, and business analysts.
Journal ArticleDOI
Big Data Analytics and Firm Performance in the Hotel Sector
TL;DR: In this paper , the authors determine which factors encourage the use of big data analytics (BD) by hotel firms and the impact of BDA on hotel firms' performance, and they also indicate that BDA can create business value by increasing the main dimensions of hotel performance: financial performance, customer retention rate and hotel reputation.
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Potrzeby analityczne polskich firm a Big Data
Proceedings ArticleDOI
Challenges in Causal Inference from Personal Monitoring Devices
TL;DR: This paper overviews existing approaches to causal inference including recent works that attempt to take advantage of time series data to automatically derive causality using extended differencein-deference or Granger methods, and outlines challenges and opportunities.
References
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Book
Big data: The next frontier for innovation, competition, and productivity
TL;DR: The amount of data in the authors' world has been exploding, and analyzing large data sets will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey.
Book
Consilience: The Unity of Knowledge
TL;DR: One of the world's greatest living scientists argues for the fundamental unity of all knowledge and the need to search for consilience, the composition of the principles governing every branch of learning.
Journal ArticleDOI
Getting Counted: Markets, Media, and Reality:
TL;DR: In this paper, the authors show that early entrants benefit from inviting coverage that makes a few-but not too many-links to other entrants, thus helping audiences perceive an emerging category.
Proceedings ArticleDOI
Understanding the value of (big) data
TL;DR: A simple taxonomy is introduced, rights to access are discussed and the case of big data as a common pool resource is analyzed.