scholarly journals Effects of Renewable Energies and Big Data on the Biggest Spanish Energy Power Companies’ Business Models

2020 ◽  
Vol 12 (1) ◽  
pp. 42-48
Author(s):  
Pablo de Mergelina
2019 ◽  
Author(s):  
Johannes Becker ◽  
Joachim Englisch ◽  
Deborah Schanz
Keyword(s):  
Big Data ◽  

2021 ◽  
pp. 097226292110225
Author(s):  
Shobhana Chandra ◽  
Sanjeev Verma

Big data (BD) is making advances in promoting sustainable consumption behaviour and has attracted the attention of researchers worldwide. Despite the increased focus, the findings of studies on this topic are fragmented, and future researchers need a systematic understanding of the existing literature for identification of the research scope. This study offers a systematic review of the role of BD in promoting sustainable-consumption behaviour with the help of a bibliometric analysis, followed by a thematic analysis. The findings suggest that businesses deploy BD to create sustainable consumer experiences, predict consumer buying patterns, design and alter business models and create nudges for sustainable consumption, while consumers are forcing businesses to develop green operations and supply chains to reduce the latter’s carbon footprint. The major research gaps for future researchers are in the following areas: the impact of big data analytics (BDA) on consumerism, the role of BD in the formation of sustainable habits and consumer knowledge creation for sustainable consumption and prediction of green consumer behaviour.


Author(s):  
David Berry

AbstractHealthcare is fully embracing the promise of Big Data for improving performance and efficiency. Such a paradigm shift, however, brings many unforeseen impacts both positive and negative. Healthcare has largely looked at business models for inspiration to guide model development and practical implementation of Big Data. Business models, however, are limited in their application to healthcare as the two represent a complicated system versus a complex system respectively. Healthcare must, therefore, look toward other examples of complex systems to better gauge the potential impacts of Big Data. Military systems have many similarities with healthcare with a wealth of systems research, as well as practical field experience, from which healthcare can draw. The experience of the United States Military with Big Data during the Vietnam War is a case study with striking parallels to issues described in modern healthcare literature. Core principles can be extracted from this analysis that will need to be considered as healthcare seeks to integrate Big Data into its active operations.


2018 ◽  
Vol 6 (4) ◽  
pp. 39-47 ◽  
Author(s):  
Reuben Ng

Cloud computing adoption enables big data applications in governance and policy. Singapore’s adoption of cloud computing is propelled by five key drivers: (1) public demand for and satisfaction with e-government services; (2) focus on whole-of-government policies and practices; (3) restructuring of technology agencies to integrate strategy and implementation; (4) building the Smart Nation Platform; (5) purpose-driven cloud applications especially in healthcare. This commentary also provides recommendations to propel big data applications in public policy and management: (a) technologically, embrace cloud analytics, and explore “fog computing”—an emerging technology that enables on-site data sense-making before transmission to the cloud; (b) promote regulatory sandboxes to experiment with policies that proactively manage novel technologies and business models that may radically change society; (c) on the collaboration front, establish unconventional partnerships to co-innovate on challenges like the skills-gap—an example is the unprecedented partnership led by the Lee Kuan Yew School of Public Policy with the government, private sector and unions.


Web Services ◽  
2019 ◽  
pp. 2161-2171
Author(s):  
Miltiadis D. Lytras ◽  
Vijay Raghavan ◽  
Ernesto Damiani

The Big Data and Data Analytics is a brand new paradigm, for the integration of Internet Technology in the human and machine context. For the first time in the history of the human mankind we are able to transforming raw data that are massively produced by humans and machines in to knowledge and wisdom capable of supporting smart decision making, innovative services, new business models, innovation, and entrepreneurship. For the Web Science research, this is a new methodological and technological spectrum of advanced methods, frameworks and functionalities never experienced in the past. At the same moment communities out of web science need to realize the potential of this new paradigm with the support of new sound business models and a critical shift in the perception of decision making. In this short visioning article, the authors are analyzing the main aspects of Big Data and Data Analytics Research and they provide their own metaphor for the next years. A number of research directions are outlined as well as a new roadmap towards the evolution of Big Data to Smart Decisions and Cognitive Computing. The authors do hope that the readers would like to react and to propose their own value propositions for the domain initiating a scientific dialogue beyond self-fulfilled expectations.


Web Services ◽  
2019 ◽  
pp. 882-903
Author(s):  
Izabella V. Lokshina ◽  
Barbara J. Durkin ◽  
Cees J.M. Lanting

The Internet of Things (IoT) provides the tools for the development of a major, global data-driven ecosystem. When accessible to people and businesses, this information can make every area of life, including business, more data-driven. In this ecosystem, with its emphasis on Big Data, there has been a focus on building business models for the provision of services, the so-called Internet of Services (IoS). These models assume the existence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated by any party. Different business models may support opportunities that generate revenue and value for various types of customers. This paper contributes to the literature by considering business models and opportunities for third-party data analysis services and discusses access to information generated by third parties in relation to Big Data techniques and potential business opportunities.


Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1677 ◽  
Author(s):  
Juan Carlo Intriago Zambrano ◽  
Jaime Michavila ◽  
Eva Arenas Pinilla ◽  
Jan Carel Diehl ◽  
Maurits W. Ertsen

Water pumping systems driven by renewable energies are more environmentally sound and, at times, less expensive alternatives to electric- or diesel-based ones. From these, hydro-powered pumps have further advantages. Nevertheless, these seem to be largely ignored nowadays. More than 800 scientific and nonscientific documents contributed to assemble their fragmented storylines. A total of 30 pressure-based hydro-powered pumping technologies worldwide have been classified and plotted in space and time. Although these do not present identifiable patterns, some noticeable clusters appear in regions such as Europe, South–Southeast Asia, and Eastern Africa, and in timeframes around 1960–1990, respectively. Some technologies have had a global impact and interest from their beginnings until contemporary times, others have been crucial for the development of specific countries, and other ones barely had almost imperceptible lives. All of them, nonetheless, have demonstrated to be a sound alternative to conventional pumping technologies, which can be unaffordable or inaccessible, particularly in remote and off-the-grid areas. Currently, hydro-powered pumping technologies face a regained momentum, hence a potentially promising future. However, researchers, manufacturers, and users need to be aware of the importance that management systems, as well as business models, pose for these technologies beyond their mere performance.


2015 ◽  
pp. 65-80 ◽  
Author(s):  
Vincenzo Morabito
Keyword(s):  
Big Data ◽  

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