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Critical analysis of Big Data challenges and analytical methods

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TLDR
In this article, the authors present a state-of-the-art review that presents a holistic view of the BD challenges and BDA methods theorized/proposed/employed by organizations to help others understand this landscape with the objective of making robust investment decisions.
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This article is published in Journal of Business Research.The article was published on 2017-01-01 and is currently open access. It has received 1267 citations till now. The article focuses on the topics: Analytics & Big data.

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Analyzing the impact of user-generated content on B2B Firms' stock performance: Big data analysis with machine learning methods

TL;DR: In this paper, the authors investigate whether UGC has differential impacts on stock performance for B2B and B2C firms by using big data and find that UGC had a significant impact on firms' stock performance.
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An Ethics Framework for Big Data in Health and Research

TL;DR: An Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health and Policy-relevant Ethics in Singapore (SHAPES) Initiative is presented, supported by the underlying ethical concerns that relate to all health and research contexts.
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Mobile supply chain management in the Industry 4.0 era: An annotated bibliography and guide for future research

TL;DR: To identify avenues for future research in mobile supply chain management (mSCM) in the advent of Industry 4.0, a systematic literature review was used to identify, classify, and analyze current knowledge, identify trends, and propose recommendations for futureResearch.
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Evaluation of collaborative consumption of food delivery services through web mining techniques

TL;DR: In this paper, the authors evaluate the impact of traffic conditions on key performance indicators of online food delivery services (through the use of web scraping techniques to retrieve customer's ratings and the physical location of restaurants as provided by Facebook).
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Can big data improve firm decision quality? The role of data quality and data diagnosticity

TL;DR: The findings show that big data utilization does not significantly impact the quality of firm decisions and it is fully mediated through DQ and data diagnosticity, contributing to practice by providing important guidelines for managers to improve firm decision quality through the use of big data.
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Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review

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Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review

TL;DR: In this article, the authors evaluate the process of systematic review used in the medical sciences to produce a reliable knowledge stock and enhanced practice by developing context-sensitive research and highlight the challenges in developing an appropriate methodology.
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Business intelligence and analytics: from big data to big impact

TL;DR: This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A, and introduces and characterized the six articles that comprise this special issue in terms of the proposed BI &A research framework.
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Beyond the hype

TL;DR: The need to develop appropriate and efficient analytical methods to leverage massive volumes of heterogeneous data in unstructured text, audio, and video formats is highlighted and the need to devise new tools for predictive analytics for structured big data is reinforced.
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