Big data in policy making

Aragona, Biagio; Rosa, Rosanna De

doi:10.1080/08898480.2017.1418113

Cited by 14 publications

(13 citation statements)

References 29 publications

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“…At present, most of the areas of business are linked to big data. It has significant influence on various perspectives of business such as business process management, human resources management, R&D management [8,63], business analytics [19,26,42,59,63], B2B business process, marketing, and sales [30,39,53,58], industrial manufacturing process [7,15,40], enterprise's operational performance measurement [20,69,81], policy making [2], supply chain management, decision, and performance [4,38,64], and so other business arenas.…”

Section: Literature Reviewmentioning

confidence: 99%

Current landscape and influence of big data on finance

2020

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In the age of technological innovation, various types of data are available with the advance of information technologies, and data is seen as one of the most valuable commodities in managing automation systems [13, 68]. In this sense, financial markets and technological evolution have become related to every human activity in the past few decades. Big data technology has become an integral part of the financial services industry and will continue to drive future innovation [12]. Financial innovations are also considered the fastest emerging issues in financial services. More specifically, they cover a variety of financial businesses such as online peer-to-peer lending, crowd-funding platforms, SME finance, wealth management and asset management platforms, trading management, crypto-currency, money/remittance transfer, mobile payments platforms, and so on. All of these services create thousands of pieces of data every day. Therefore,

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Section: Literature Reviewmentioning

confidence: 99%

Current landscape and influence of big data on finance

2020

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“…At present, most of the business areas are connected to big data. Big data has a critical effect on different dimensions of businesses, for example, in terms of human resources management, research, and development [27,28]; management processes [27,[29][30][31]; business to business processes, advertising, and marketing [32,33]; mechanical assembling measures [34][35][36]; enterprises' operational performance [36,37]; policy-making [38]; and supply chain management [38,39]. In particular, Rabhi, Falih [27] referenced big data as a noteworthy factor of business measure management and HR cycles to help in the decision-making process.…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying Big Data’s Opportunities, Challenges, and Implications in Finance

et al. 2020

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One of the latest innovations in business and technology is the use of big data, as daily data are generated by billions of events. The big data issue is now considered in the accountants and finance professionals’ field as one of the most important sources for the analysis of financial products and services. This study is very innovative, with our research aiming to identify the opportunities, challenges, and implications of big data in the finance area. It is our purpose to find competitive advantages in terms of the extent to which big data brings visible benefits, also pointing out the challenges that a company may face in this field, such as cases of customers’ data security or customer satisfaction processes. The identification of this kind of dynamics allows us to draw conclusions on the advantages of big data based on these analyses and big data’s deep impact on finance. In particular, big data is now commonly used by financial institutions and banks for analytical purposes in financial market contexts. We conducted an exploratory survey of the existing literature to highlight such connections. In the last part of our study, we also propose directions for future research.

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“…In other words, an algorithm is the mathematization of a process understood in terms of an if-then mechanism, which allows of the management of the flow of data and its processing. Thus, the implementation of such techniques and algorithms permits processing structured data, semi-structured data, and unstructured data (Holmes, 2017;Aragona and de Rosa, 2018). In this manner, we have to comprehend the difference among all these kinds of data.…”

Section: The Concept Of Big Datamentioning

confidence: 99%

“…Additionally, semi-structured data must be understood as the data that involve "Narratives, texts, and images" (Aragona and de Rosa, 2018). This type of data implies some degree of structuration as long as these data are "included by the user" (Aragona and de Rosa, 2018, 3) -a particular user.…”

Section: The Concept Of Big Datamentioning

confidence: 99%

The Onto-epistemology of Big Data

Vargas

2020

Sapientiae

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This study puts forward the results of a comprehensive literature review that allows of the exploration of the big data phenomenon as in technical terms as well in socio-political and philosophical ones, through the reading of authors such as Rob Kitchin (2014), Dawn E. Holmes (2017), and so forth. It is here offered a new critical approach to Big Data as long as the analysis have permitted us to evaluate not only the components of this new data science, but also the onto-epistemological consequences derived from the development and implementation of Big Data as in the scientific field as well in the quotidian. Also, this paper permits us to understand the linkage between Big Data and set theory in the construction of an onto-epistemology related to a political conservatism so that we are able to have the complete panorama in order to elaborate, in the near future, strategies to sublate such a phenomenon.

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Big data in policy making

Cited by 14 publications

References 29 publications

Current landscape and influence of big data on finance

Current landscape and influence of big data on finance

Identifying Big Data’s Opportunities, Challenges, and Implications in Finance

The Onto-epistemology of Big Data

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