Much- needed business digital transformation through big data, internet of things and blockchain capabilities: implications for strategic performance in telecommunication sector

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anam Bhatti ◽  
Haider Malik ◽  
Ahtisham Zahid Kamal ◽  
Alamzeb Aamir ◽  
Lamya Abdulrahman Alaali ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Quality ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Digital Transformation ◽  
Equation Modeling ◽  
Content Type ◽  
Strategic Performance ◽  
Dependent Variables

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.

Effect of big data analytics on improvement of corporate social/green performance

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bibhu Prasad Mishra ◽  
Bibhuti Bhusan Biswal ◽  
Ajay Kumar Behera ◽  
Harish Chandra Das
Keyword(s):  
Big Data ◽  
Corporate Culture ◽  
Data Analytics ◽  
Corporate Social Performance ◽  
Big Data Analytics ◽  
Equation Modeling ◽  
Content Type ◽  
Green Performance ◽  
Corporate Social ◽  
Control Direction

Purpose In spite of the fact that literature shows that big data analytics (BDA) pass on a distinct corporate ability, little is thought about their performance impacts, specifically logical conditions. Establishing this research in the dynamic capability view (DCV) and corporate culture and dependent on an sample of 310 Indian production industries, the purpose of this paper is to experimentally study the impacts of BDA on corporate social performance (CSP) and corporate green performance (CGP) using variance-based structural equation modeling (for example, PLS). Design/methodology/approach A questionnaire was used to accumulate data sets to examine research hypothesis. The authors pre-examined the survey with six scholastics and six directors from production firms in India. With the help of their sources of data, the authors have adjusted their wordings to improve the transparency and guarantee that length of the survey is accurate. Finally, the questionnaire was prepared for definite data collection. Findings The authors conclude that BDA has noteworthy effect on CSP/CGP. Notwithstanding, the authors did not find proof for directing role of flexible direction and control direction in the connections among BDA and CSP/CGP. This research offers a more nuanced comprehension of the performance ramifications of BDA, and in this way, it is tending to the critical inquiries of how and when BDA can improve in supply chains. Originality/value This investigation makes helpful commitments to the BDA research and its effect on CSP/CGP. To the authors’ best of information, this is the first hypothesis-focused approach to clarify the effect of BDA on ecological and social supportability. Second, this investigation likewise gives empirical proof that BDA impact on CSP/CGP and is free of flexible or control direction of the industry.

Mediating effect of big data analytics on project performance of small and medium enterprises

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin K. Mangla ◽  
Rakesh Raut ◽  
Vaibhav S. Narwane ◽  
Zuopeng (Justin) Zhang ◽  
Pragati priyadarshinee
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Project Performance ◽  
Mediating Effect ◽  
Equation Modeling ◽  
Content Type ◽  
Operational Capabilities ◽  
Green Purchasing

PurposeThis study aims to investigate the mediating role of “Big Data Analytics” played between “Project Performance” and nine factors including top management, project knowledge management focus on sustainability, green purchasing, environmental technologies, social responsibility, project operational capabilities, project complexity, collaboration and explorative learning, and project success.Design/methodology/approachA sample of 321 responses from 106 Indian manufacturing small and medium-scaled enterprises (SMEs) was collected. Data were analyzed using empirical analysis through structural equation modeling.FindingsThe result shows that project knowledge management, green purchasing and project operational capabilities require the mediating support of big data analytics. The adoption of big data analytics has a positive influence on project performance in the manufacturing sector.Practical implicationsThis study is useful to SMEs managers, practitioners and government policymakers to develop an understanding of big data analytics, eliminate challenges in the adoption of big data, and formulate strategies to handle projects efficiently in SMEs in the context of Indian manufacturing.Originality/valueFor the first time, big data for manufacturing firms handing innovative projects was discussed in the Indian SME context.

scholarly journals Significance of Technology and Digital Transformation in Shaping the Future of Oil and Gas Industry

2021 ◽  
Vol 12 (3) ◽  
pp. 3345-3352
Author(s):  
Shubham Parsoya Et.al
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Oil And Gas ◽  
Big Data Analytics ◽  
Oil And Gas Industry ◽  
Digital Transformation ◽  
Gas Industry ◽  
The Future

Digital transformation in the field of oil and Gas industry is already a significant impact creator. It is actually act like catalyst through which the overall functionality of the oil and gas industry get enhanced and the overall output with the help of technologically-advanced mechanism, increased up to manifold. In the present scenario, the over-all quest is not just about the volume of the oil and petroleum, but it is also regarding the overall value generated throughout the process. And such enhanced level of value generation is taking place with great pace with the help of enhanced level of implementations of different types of technologies in different type of activities related to the oil and gas industry. In the present scenario, oil and gas industry’s business model is no longer depending upon just the inflated and narrow based value-chain mechanism. It is actually depending upon the almost all modernized and futuristic technologies. The modern technologies include big data analytics, 3D printing technology, cyber security, digital marketing, Artificial Intelligence, Internet of Things, drone technologies, database management system, etc. all these technologies are not only supports in handling the overall business capability of the oil and Gas Industries, but also eliminate the overall negative impact generating elements. With the help of technologies and digital transformation, the overall profitability of the oil and gas industry enhanced. Digital transformation is a prominent and significant impact creator which is not limited to the oil and gas industry, but also reaching up to the all-global level Businesses. It is transforming the overall business operations by enhancing the speed of innovation and making the use of practical knowledge base which ultimately enhance the overall power of operations and increase efficiencies. With the emergence of digital transformation technologies especially with the emergence of big data analytics, the Internet of Things and Artificial Intelligence have supports several types of innovative and new ways of developing and transforming the overall market as well as the customer satisfaction in significant manner. All such innovative technologies and digital transformations are contributing significantly in shaping the future of oil and gas industry

Consequential factors of Big Data's Analytics Capability: how firms use data in the competitive scenario

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Luis Hernan Contreras Pinochet ◽  
Guilherme de Camargo Belli Amorim ◽  
Durval Lucas Júnior ◽  
Cesar Alexandre de Souza
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Structural Equation ◽  
Explanatory Power ◽  
Big Data Analytics ◽  
Strategic Decision ◽  
Analytical Models ◽  
Equation Modeling ◽  
Content Type ◽  
Analytics Capability

PurposeThe article's objective is to analyze the consequent factors of Big Data Analytics Capability for firms in the competitive scenario, using different analytical models.Design/methodology/approachThe research had a quantitative approach, using a survey of data from firms located in the state of São Paulo – Brazil. Structural Equation Modeling (SEM) was used to validate the model.FindingsThe results reveal that all hypotheses were accepted. Business value was the construct that had the most explanatory power in the model. It is necessary to invest more in analytical tools, as well as people trained in the analysis of these models, in addition to a change of mindset, which will dictate the bias of the firm's strategic decision-making. The Big Data analysis is evident from firms' growing investments, particularly those that operate in complex and fast-paced environments.Practical implicationsThe proposed theoretical model makes it possible to verify firms' analytical structure and whether they are better positioned to analyze customer data and information in real-time, generate insights and implement solutions to maintain and improve their market position.Originality/valueThe contribution of this article is to present a proposal to expand the research models in the literature that analyzed the direct and indirect relationship between “Big Data Analytics Capability” and “Product Innovation Performance”.

Dave Snowden on KM and big data/analytics: interview with David J. Pauleen

2017 ◽  
Vol 21 (1) ◽  
pp. 12-17 ◽  
Author(s):  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Theory And Practice ◽  
Content Type ◽  
Face To Face ◽  
The Relationship ◽  
A Company ◽  
Practical Implications ◽  
Scientific Officer

Purpose Dave Snowden has been an important voice in knowledge management over the years. As the founder and chief scientific officer of Cognitive Edge, a company focused on the development of the theory and practice of social complexity, he offers informative views on the relationship between big data/analytics and KM. Design/methodology/approach A face-to-face interview was held with Dave Snowden in May 2015 in Auckland, New Zealand. Findings According to Snowden, analytics in the form of algorithms are imperfect and can only to a small extent capture the reasoning and analytical capabilities of people. For this reason, while big data/analytics can be useful, they are limited and must be used in conjunction with human knowledge and reasoning. Practical implications Snowden offers his views on big data/analytics and how they can be used effectively in real world situations in combination with human reasoning and input, for example in fields from resource management to individual health care. Originality/value Snowden is an innovative thinker. He combines knowledge and experience from many fields and offers original views and understanding of big data/analytics, knowledge and management.

Big data analytics for 6G enabled massive Internet of Things

2021 ◽  
pp. 1-1
Author(s):  
Zhihan Lv ◽  
Ranran Lou ◽  
Jinhua Li ◽  
Amit Kumar Singh ◽  
Houbing Song
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics
Sign in / Sign up

Export Citation Format

Share Document