Data quality management, data usage experience and acquisition intention of big data analytics

PurposeIn the field of business, digital transformation is the integration of digital technology into all areas of business, from generating to deliver value to customers. This concept is essential for sustainable growth of a company and its overall economy. Based on this fact, this authentic and informative research is conducted whose major aim is to examine the importance of digital transformation within a business through big data, the Internet of things and blockchain-based capabilities for overall strategic performance within the telecom sector in China.Design/methodology/approachFor that aim, data quality and technology competence are considered as independent variables, strategic performance as dependent variable and big data analytics capabilities, Internet of things capabilities and blockchain capabilities routinization acted as mediators within this paper. In its data collection mechanism, an online survey was conducted in which questionnaires are randomly distributed to the telecom sector's professionals in which only 343 of them gave their valid outcomes. After collecting primary data, confirmatory factor analysis (CFA) and structural equation modeling (SEM)–based statistical outcomes have been generated.FindingsResults indicate that there is a significant relationship between data quality and strategic performance and between technological competence and strategic performance. Also, the big data analytics and Internet of Things capabilities acted as significant mediating role between both independent and dependent variables. But blockchain capabilities routinization is that variable that acts as an insignificant mediator between independent and dependent variables' relationship.Originality/valueOverall, this study is an informative and attractive source for the Chinese government, its telecom industry, administrative body and related ones to understand the importance of such IT capabilities' implications within their operating activities for their strategic performance management. Also, related field scholars can utilize its reliable data in their research analysis. Its major limitations are (1) lack of qualitative/ mixed method of research and (2) lack of comparative analysis that may impact the acceptability factor of this paper, and this weakness can be overcome by upcoming scholars in their research.

Download Full-text

Abstract 2605: Improving data quality in oncology immunotherapy clinical research by big data analytics and data visualization

10.1158/1538-7445.am2017-2605 ◽

2017 ◽

Author(s):

Chengsen Xue ◽

Joanne Cuomo ◽

Walter Meyers ◽

Thomas W. Mc Closkey

Keyword(s):

Big Data ◽

Clinical Research ◽

Data Quality ◽

Data Visualization ◽

Data Analytics ◽

Big Data Analytics

Download Full-text

Eco-Innovation and Industry 4.0: A Big Data Usage conceptual model

SHS Web of Conferences ◽

10.1051/shsconf/20185605003 ◽

2018 ◽

Vol 56 ◽

pp. 05003 ◽

Cited By ~ 1

Author(s):

Russell Tatenda Munodawafa ◽

Satirenjit Kaur Johl

Keyword(s):

Big Data ◽

Industry 4.0 ◽

Data Analytics ◽

Big Data Analytics ◽

Digital Economy ◽

Future Research ◽

New Era ◽

Data Usage ◽

The World ◽

Development Goals

Driven by Cyber Physical Systems, Big Data Analytics, Internet of Things and Automation, Industry 4.0 is expected to revolutionize the world. A new era beckons for enterprises of all sizes, markets, governments, and the world at large as the digital economy fully takes off under Industry 4.0. The United Nations has also expressed its desire to usher in a new era for humanity with the Sustainable Development Goals 2030 (SDG’s) replacing the Millennial Development Goals (MDG’s). Critical to the achievement of both of the above-mentioned ambitions is the efficient and sustainable use of natural resources. Big Data Analytics, an important arm of Industry 4.0, gives organizations the ability to eco-innovate from a resource perspective. This paper conducts an analysis of previously published research literature and contributes to this emerging research area looking at Big Data Usage from a strategic and organizational perspective. A conceptual framework that can be utilized in future research is developed from the literature. Also discussed is the expected impact of Big Data Usage towards firm performance, particularly as the world becomes more concerned about the environment. Data driven eco-innovation should be in full motion if organizations are to remain relevant in tomorrow’s potentially ultra-competitive digital economy.

Download Full-text