scholarly journals Conceptualization and theorization of the Big Data

2016 ◽  
Vol 4 (2) ◽  
pp. 23-41 ◽  
Author(s):  
Marcos Mazzieri ◽  
Eduardo Dantas Soares
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Value Creation ◽  
Extensive Literature ◽  
Resource Based View ◽  
Business Innovation ◽  
Knowledge Database ◽  
Conceptual Definition ◽  
Bibliometric Studies ◽  
Or Applications

The term Big Data is being used widely by companies and researchers who consider your relevant functionalities or applications to create value and business innovation. However some questions arise about what is this phenomenon and, more precisely, how it occurs and under what conditions it can create value and innovation in business. In our view, the lack of depth related to the principles involved in Big Data and the very absence of a conceptual definition, made it difficult to answer these questions that have been the basis for our research. To answer these questions we did a bibliometric study and extensive literature review. The bibliometric studies were realized based in articles and citation of Web of Knowledge database. The main result of our research is the providing a conceptual definition for the term Big Data. Also, we propose which principles discovered can contribute with other researches  that intend value creation by Big Data. Finally we propose see the value creation through Big Data using the  Resource Based View as the main theory used for discuss that theme.

scholarly journals Assessing the Role of Big Data and the Internet of Things on the Transition to Circular Economy: Part I : An extension of the ReSOLVE framework proposal through a literature review

2020 ◽  
Vol 64 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Gustavo Cattelan Nobre ◽  
Elaine Tavares
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Literature Review ◽  
Circular Economy ◽  
Grey Literature ◽  
Modern Technology ◽  
The Internet ◽  
Extensive Literature ◽  
Statistical Tool ◽  
The Internet Of Things

The debate about circular economy (CE) is increasingly present in the strategic agenda of organisations around the world, being driven by government agencies and general population pressures, or by organisations’ own vision for a sustainable future. This is due in part to the increasing possibility of turning original theoretical CE proposals into real economically viable initiatives, now possible with modern technology applications such as big data and the internet of things (IoT). Information technology (IT) professionals have been called upon to incorporate technology projects into their strategic plans to support their organisations’ transition to CE, but a structured framework with the necessary IT capabilities still lacks. This study focuses on taking the first step towards this path, by extending the technology attributes present on the existing Ellen MacArthur Foundation (EMF) Regenerate, Share, Optimise, Loop, Virtualise and Exchange (ReSOLVE) framework. The research was conducted based on an extensive literature review through 226 articles retrieved from Scopus® and Web of ScienceTM databases, which were triangulated, validated and complemented with content analysis using the ‘R’ statistical tool, grey literature research and inputs from specialists. Part I describes the introduction and methods used in this study.

A selected literature review on the changing role of stakeholders as value creators

2016 ◽  
Vol 13 (2) ◽  
pp. 100-119 ◽  
Author(s):  
Shridhar M Samant ◽  
Shirish Sangle
Keyword(s):  
Text Mining ◽  
Literature Review ◽  
Value Creation ◽  
Extensive Literature ◽  
Content Type ◽  
Novel Approach ◽  
Sustainable Value ◽  
New Research ◽  
Changing Role

Purpose – The purpose of this paper is to investigate the changing role of stakeholders in value creation since the inception of literature on stakeholders and sustainability from 1984 and 1987, respectively until 2015. To understand interrelationships among key terms of stakeholder and sustainability literature. Design/methodology/approach – The paper explores the changing role of stakeholders as a source of value creation through extensive literature review by adopting text mining approach. VantagePoint is the tool used to facilitate text mining literature of sustainability and stakeholder and related literature from 1984 to 2015. Findings – This paper reveals that the major trends in firm’s approach towards stakeholders has changed over the years from demonstration of compliance in 1984-1994, safeguarding of reputation from 1994 to 2004, to finally co-creating value with stakeholders from the period of 2004-2014. Research limitations/implications – There have been extensive literature reviews done on stakeholder and sustainability literature, but only few have studied the integration of stakeholder and sustainability literature. This paper has used a novel approach, i.e. VantagePoint software to analyse the sustainability and stakeholder literature. Originality/value – The changing role of stakeholders as a value creator have provided new research avenues in value creation process. The emerging challenge that firms now face is to co-create sustainable value by engaging both internal and external stakeholders.

scholarly journals Data-driven smart eco-cities and sustainable integrated districts: A best-evidence synthesis approach to an extensive literature review

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Simon Elias Bibri
Keyword(s):  
Big Data ◽  
Literature Review ◽  
Urban Ecology ◽  
Smart Cities ◽  
Evidence Synthesis ◽  
Data Driven ◽  
Extensive Literature ◽  
Best Evidence Synthesis ◽  
Big Data Technologies ◽  
Smart Urbanism

AbstractAs materializations of trends toward developing and implementing urban socio-technical and enviro-economic experiments for transition, eco-cities have recently received strong government and institutional support in many countries around the world due to their ability to function as an innovative strategic niche where to test and introduce various  reforms. There are many models of the eco-city based mainly on either following the principles of urban ecology or combining the strategies of sustainable cities and the solutions of smart cities. The most prominent among these models are sustainable integrated districts and data-driven smart eco-cities. The latter model represents the unprecedented transformative changes the eco-city is currently undergoing in light of the recent paradigm shift in science and technology brought on by big data science and analytics.  This is motivated by the growing need to tackle the problematicity surrounding eco-cities in terms of their planning, development, and governance approaches and practices. Employing a combination of both best-evidence synthesis and narrative approaches, this paper provides a comprehensive state-of-the-art and thematic literature review on sustainable integrated districts and data-driven smart eco-cities. The latter new area is a significant gap in and of itself that this paper seeks to fill together with to what extent the integration of eco-urbanism and smart urbanism is addressed in the era of big data, what driving factors are behind it, and what forms and directions it takes. This study reveals that eco-city district developments are increasingly embracing compact city strategies and becoming a common expansion route for growing cities to achieve urban ecology or urban sustainability. It also shows that the new eco-city projects are increasingly capitalizing on data-driven smart technologies to implement environmental, economic, and social reforms. This is being accomplished by combining the strengths of eco-cities and smart cities and harnessing the synergies of their strategies and solutions in ways that enable eco-cities to improve their performance with respect to sustainability as to its tripartite composition. This in turn means that big data technologies will change eco-urbanism in fundamental and irreversible ways in terms of how eco-cities will be monitored, understood, analyzed, planned, designed, and governed. However, smart urbanism poses significant risks and drawbacks that need to be addressed and overcome in order to achieve the desired outcomes of ecological sustainability in its broader sense. One of the key critical questions raised in this regard pertains to the very potentiality of the technocratic governance of data-driven smart eco-cities and the associated negative implications and hidden pitfalls. In addition, by shedding light on the increasing adoption and uptake of big data technologies in eco-urbanism, this study seeks to assist policymakers and planners in assessing the pros and cons of smart urbanism when effectuating ecologically sustainable urban transformations in the era of big data, as well as to stimulate prospective research and further critical debates on this topic.

Semantic (Big) Data Analysis: an Extensive Literature Review

2019 ◽  
Vol 17 (05) ◽  
pp. 796-806 ◽  
Author(s):  
Hector H. Guedea Noriega ◽  
Francisco Garcia Sanchez
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Literature Review ◽  
Big Data Analysis ◽  
Extensive Literature ◽  
Extensive Literature Review

scholarly journals Value Modeling for Ecosystem Analysis

Computers ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 68 ◽  
Author(s):  
Alejandro Arreola González ◽  
Matthias Pfaff ◽  
Helmut Krcmar
Keyword(s):  
Literature Review ◽  
Value Creation ◽  
Comprehensive Overview ◽  
Business Innovation ◽  
Integrative Framework ◽  
Modeling Techniques ◽  
Limited Support ◽  
Value Modeling ◽  
Platform Ecosystems ◽  
Structured Literature Review

Scholars have proposed many approaches to represent and analyze value creation. Value creation in ecosystems such as platform ecosystems often relies on a specific structure of partner alignment. Value modeling techniques can improve the understanding of how ecosystem risks and non-generic complementarities determine value creation and the alignment structures required. First, we conceptualize ecosystem analysis as a tool for alignment in the context of business innovation. Then, we carry out a structured literature review to identify existing techniques, which could support ecosystem analysis. Further, we provide a comprehensive overview of the value modeling techniques and integrate our ecosystem analysis conceptualization with existing classification frameworks. This integrative framework allows researchers and scholars to identify techniques that suit specific needs in terms of internal alignment reach, tooling, innovation phase and ecosystem analysis. Our results show limited support for ecosystem analysis. Still we are able to identify techniques that can provide a useful conceptual or tooling basis to enable ecosystem analysis.

Trends and Opportunities in Health Analytics as a Service and Implications for Use in Low Resource Settings: A Literature Review Abstract (Preprint)

2019 ◽  
Author(s):  
Meghana Bastwadkar ◽  
Carolyn McGregor ◽  
S Balaji
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Intensive Care ◽  
Literature Review ◽  
Health Monitoring ◽  
Data Analytics ◽  
Neonatal Intensive Care ◽  
Big Data Analytics ◽  
Healthcare Facilities

BACKGROUND This paper presents a systematic literature review of existing remote health monitoring systems with special reference to neonatal intensive care (NICU). Articles on NICU clinical decision support systems (CDSSs) which used cloud computing and big data analytics were surveyed. OBJECTIVE The aim of this study is to review technologies used to provide NICU CDSS. The literature review highlights the gaps within frameworks providing HAaaS paradigm for big data analytics METHODS Literature searches were performed in Google Scholar, IEEE Digital Library, JMIR Medical Informatics, JMIR Human Factors and JMIR mHealth and only English articles published on and after 2015 were included. The overall search strategy was to retrieve articles that included terms that were related to “health analytics” and “as a service” or “internet of things” / ”IoT” and “neonatal intensive care unit” / ”NICU”. Title and abstracts were reviewed to assess relevance. RESULTS In total, 17 full papers met all criteria and were selected for full review. Results showed that in most cases bedside medical devices like pulse oximeters have been used as the sensor device. Results revealed a great diversity in data acquisition techniques used however in most cases the same physiological data (heart rate, respiratory rate, blood pressure, blood oxygen saturation) was acquired. Results obtained have shown that in most cases data analytics involved data mining classification techniques, fuzzy logic-NICU decision support systems (DSS) etc where as big data analytics involving Artemis cloud data analysis have used CRISP-TDM and STDM temporal data mining technique to support clinical research studies. In most scenarios both real-time and retrospective analytics have been performed. Results reveal that most of the research study has been performed within small and medium sized urban hospitals so there is wide scope for research within rural and remote hospitals with NICU set ups. Results have shown creating a HAaaS approach where data acquisition and data analytics are not tightly coupled remains an open research area. Reviewed articles have described architecture and base technologies for neonatal health monitoring with an IoT approach. CONCLUSIONS The current work supports implementation of the expanded Artemis cloud as a commercial offering to healthcare facilities in Canada and worldwide to provide cloud computing services to critical care. However, no work till date has been completed for low resource setting environment within healthcare facilities in India which results in scope for research. It is observed that all the big data analytics frameworks which have been reviewed in this study have tight coupling of components within the framework, so there is a need for a framework with functional decoupling of components.

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