scholarly journals Strategic Key Elements in Big Data Analytics as Driving Forces of IoT Manufacturing Value Creation: A Challenge for Research Framework

2021 ◽  
pp. 1-16
Author(s):  
Rastislav Rajnoha ◽  
Jakub Hadac
Keyword(s):  
Big Data ◽  
Value Creation ◽  
Data Analytics ◽  
Driving Forces ◽  
Big Data Analytics ◽  
Research Framework

scholarly journals Use cases and challenges in telecom big data analytics

2016 ◽  
Vol 5 ◽  
Author(s):  
Chung-Min Chen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Driving Forces ◽  
Big Data Analytics ◽  
Use Cases ◽  
Telecommunication Industry ◽  
New Research

This paper examines the driving forces of big data analytics in the telecom domain and the benefits it offers. We provide example use cases of big data analytics and the associated challenges, with the hope to inspire new research ideas that can eventually benefit the practice of the telecommunication industry.

Integrating Digital Innovation Capabilities Towards Value Creation

2020 ◽  
Vol 16 (4) ◽  
pp. 37-50
Author(s):  
Sampson Abeeku Edu ◽  
Mary Agoyi ◽  
Divine Quazie Agozie
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Value Creation ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Managerial Decision ◽  
Technology Infrastructure ◽  
Digital Innovation ◽  
Information Technology Infrastructure ◽  
Operational Activities

Towards the view of value creation through digital applications integration and their complementary characteristics, this study proposes a framework using the resource-based view and the capability view to explore the integration of digital capabilities to support value creation in an organization. The paper adopted a systematic review by exploring literature on digital innovations applications such as big data analytics, cloud computing, and internet of things (IoTs). The conceptual model developed suggested that deploying digital innovation capabilities promotes organizations to benefit in the area the of managerial decision making, enhancing information technology infrastructure alignments, operational activities, and overall firm performance. This article further extends the discussions toward the need to integrate digital innovation capabilities such as IoTs, big data analytics, and cloud computing and the range of relationships existing among these innovations to support value creation for firms towards technology deployment in IS literature.

Relationships between industry 4.0, sustainable manufacturing and circular economy: proposal of a research framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Surajit Bag ◽  
Jan Harm Christiaan Pretorius
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Circular Economy ◽  
Industry 4.0 ◽  
Data Analytics ◽  
Sustainable Manufacturing ◽  
Big Data Analytics ◽  
Content Type ◽  
Research Framework ◽  
Challenges And Opportunities

Purpose The digital revolution has brought many challenges and opportunities for the manufacturing firms. The impact of Industry 4.0 technology adoption on sustainable manufacturing and circular economy has been under-researched. This paper aims to review the latest articles in the area of Industry 4.0, sustainable manufacturing and circular economy and further developed a research framework showing key paths. Design/methodology/approach Qualitative research is performed in two stages. In the first stage, a review of the extant literature is performed to identify the barriers, drivers, challenges and opportunities. In the second stage, a research framework is proposed to integrate Industry 4.0 technology (big data analytics powered artificial intelligence) adoption, sustainable manufacturing and circular economy capabilities. Findings This research extends the knowledge base by providing a detailed review of Industry 4.0, sustainable manufacturing, and circular economy and proposes a research framework by integrating these three contemporary concepts in the context of supply chain management. Through an exploration of this integrative research framework, the authors propose a future research agenda and seven research propositions. Research limitations/implications It is important to understand the interplay between institutional pressures, tangible resources and human skills for Industry 4.0 technology (big data analytics powered artificial intelligence) adoption. Industry 4.0 technology (big data analytics powered artificial intelligence) adoption can positively influence sustainable manufacturing and circular economy capabilities. Managers must also put more attention to sustainable manufacturing to develop circular economic capabilities. Social implications Factory workers and the local communities generally suffer from various adverse effects resulting from the traditional manufacturing process. The quality of the environment is deteriorating to such an extent that people even staying miles away from the factory are also affected due to environmental pollution that is generated from factory operations. Hence, sustainable manufacturing is the only choice left to manufacturers that can help in the transition to a circular economy. The research framework can help firms to enhance circular economy capabilities. Originality/value This review paper contains the most updated work on Industry 4.0, sustainable manufacturing and circular economy. It also proposes a research framework to integrate these three concepts.

Sign in / Sign up

Export Citation Format

Share Document