scholarly journals Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view

2019 ◽  
Vol 56 (6) ◽  
pp. 103135 ◽  
Author(s):  
Saqib Shamim ◽  
Jing Zeng ◽  
Syed Muhammad Shariq ◽  
Zaheer Khan
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Management ◽  
Dynamic Capabilities ◽  
Chinese Firms

Big data management and environmental performance: role of big data decision-making capabilities and decision-making quality

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qasim Ali Nisar ◽  
Nadia Nasir ◽  
Samia Jamshed ◽  
Shumaila Naz ◽  
Mubashar Ali ◽  
...  
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Management ◽  
Environmental Performance ◽  
Public Hospitals ◽  
Private Hospitals ◽  
Public And Private ◽  
Content Type ◽  
Public And Private Hospitals

PurposeThis study is undertaken to examine the antecedents and role of big data decision-making capabilities toward decision-making quality and environmental performance among the Chinese public and private hospitals. It also examined the moderating effect of big data governance that was almost ignored in previous studies.Design/methodology/approachThe target population consisted of managerial employees (IT experts and executives) in hospitals. Data collected using a survey questionnaire from 752 respondents (374 respondents from public hospitals and 378 respondents from private hospitals) was subjected to PLS-SEM for analysis.FindingsFindings revealed that data management challenges (leadership focus, talent management, technology and organizational culture for big data) are significant antecedents for big data decision-making capabilities in both public and private hospitals. Moreover, it was also found that big data decision-making capabilities played a key role to improve the decision-making quality (effectiveness and efficiency), which positively contribute toward environmental performance in public and private hospitals of China. Public hospitals are playing greater attention to big data management for the sake of quality decision-making and environmental performance than private hospitals.Practical implicationsThis study provides guidelines required by hospitals to strengthen their big data capabilities to improve decision-making quality and environmental performance.Originality/valueThe proposed model provides an insight look at the dynamic capabilities theory in the domain of big data management to tackle the environmental issues in hospitals. The current study is the novel addition in the literature, and it identifies that big data capabilities are envisioned to be a game-changer player in effective decision-making and to improve the environmental performance in health sector.

scholarly journals Characterizing Big Data Management

10.28945/2192 ◽  
2015 ◽  
Author(s):  
Rogério Rossi ◽  
Kechi Hirama
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Big Data ◽  
Data Management ◽  
Process Management ◽  
Three Dimensions ◽  
Storage And Retrieval ◽  
Human Aspects ◽  
Business Approach ◽  
Support Decision Making

[The final form of this paper was published in the journal Issues in Informing Science and Information Technology.] Considering that big data is a reality for an increasing number of organizations in many areas, its management represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial dimensions to facilitate the management of big data in any organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management must be supported by technology, people and processes; hence, this article discusses these three dimensions: the technologies for storage, analysis and visualization of big data; the human aspects of big data; and, in addition, the process management involved in a technological and business approach for big data management.

Big Data Myth

2019 ◽  
pp. 223-237
Author(s):  
Agata Mardosz-Grabowska
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Qualitative Data ◽  
New Technologies ◽  
Marketing Management ◽  
Individual Experience ◽  
Decision Making Process

Organizations are expected to act rationally; however, mythical thinking is often present among their members. It refers also to myths related to technology. New inventions and technologies are often mythologized in organizations. People do not understand how new technologies work and usually overestimate their possibilities. Also, myths are useful in dealing with ambivalent feelings, such as fears and hopes. The text focuses on the so-called “big data myth” and its impact on the decision-making process in modern marketing management. Mythical thinking related to big data in organizations has been observed both by scholars and practitioners. The aim of the chapter is to discuss the foundation of the myth, its components, and its impact on the decision-making process. Among others, a presence of a “big data myth” may be manifested by over-reliance on data, neglecting biases in the process of data analysis, and undermining the role of other factors, including intuition and individual experience of marketing professionals or qualitative data.

The Role of Big Data and Business Analytics in Decision Making

2021 ◽  
pp. 226-257
Author(s):  
Pedro Caldeira Neves ◽  
Jorge Rodrigues Bernardino
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Open Source ◽  
Specific Area ◽  
Business Analytics ◽  
Business Decision ◽  
Business Sustainability ◽  
Open Source Systems ◽  
Fundamental Shift

The amount of data in our world has been exploding, and big data represents a fundamental shift in business decision-making. Analyzing such so-called big data is today a keystone of competition and the success of organizations depends on fast and well-founded decisions taken by relevant people in their specific area of responsibility. Business analytics (BA) represents a merger between data strategy and a collection of decision support technologies and mechanisms for enterprises aimed at enabling knowledge workers such as executives, managers, and analysts to make better and faster decisions. The authors review the concept of BA as an open innovation strategy and address the importance of BA in revolutionizing knowledge towards economics and business sustainability. Using big data with open source business analytics systems generates the greatest opportunities to increase competitiveness and differentiation in organizations. In this chapter, the authors describe and analyze business intelligence and analytics (BI&A) and four popular open source systems – BIRT, Jaspersoft, Pentaho, and SpagoBI.

scholarly journals Semantics-Empowered Big Data Processing with Applications

AI Magazine ◽  
2015 ◽  
Vol 36 (1) ◽  
pp. 39-54 ◽  
Author(s):  
Krishnaprasad Thirunarayan ◽  
Amit Sheth
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Processing ◽  
Social Systems ◽  
Intelligent Processing ◽  
Data Formats ◽  
New Concepts ◽  
Semantic Models ◽  
Trust Models

We discuss the nature of big data and address the role of semantics in analyzing and processing big data that arises in the context of physical-cyber-social systems. To handle volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle variety, we resort to semantic models and annotations of data so that intelligent processing can be done independent of heterogeneity of data formats and media. To handle velocity, we seek to use continuous semantics capability to dynamically create event or situation specific models and recognize relevant new concepts, entities and facts. To handle veracity, we explore trust models and approaches to glean trustworthiness. These four v's of big data are harnessed by the semantics-empowered analytics to derive value to support applications transcending physical-cyber-social continuum.

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