Next Article in Journal
Relationships between Student Personality Traits, Mobbing, and Depression within the Context of Sustainable Tourism Education: The Case of a Faculty of Tourism
Next Article in Special Issue
A Conceptual Framework for Assessing an Organization’s Readiness to Adopt Big Data
Previous Article in Journal
Tree Species Diversity and Socioeconomic Perspectives of the Urban (Food) Forest of Accra, Ghana
Previous Article in Special Issue
(Smart) Citizens from Data Providers to Decision-Makers? The Case Study of Barcelona
Open AccessArticle

The Missing Variable in Big Data for Social Sciences: The Decision-Maker

Department of Management, Economics and Industrial Engineering, Politecnico di Milano, 20156 Milano, Italy
Sustainability 2018, 10(10), 3415; https://doi.org/10.3390/su10103415
Received: 23 August 2018 / Revised: 18 September 2018 / Accepted: 19 September 2018 / Published: 25 September 2018
(This article belongs to the Special Issue Big Data Research for Social Sciences and Social Impact)
The value of big data for social sciences and social impact is professed to be high. This potential value is related, however, to the capacity of using extracted information in decision-making. In all of this, one important point has been overlooked: when “humans” retain a role in the decision-making process, the value of information is no longer an objective feature but depends on the knowledge and mindset of end users. A new big data cycle has been proposed in this paper, where the decision-maker is placed at the centre of the process. The proposed cycle is tested through two cases and, as a result of the suggested approach, two operations—filtering and framing—which are routinely carried out independently by scientists and end users in an unconscious manner, become clear and transparent. The result is a new cycle where four dimensions guide the interactions for creating value. View Full-Text
Keywords: big data; social sciences; decision-making; data analyst; filtering; framing big data; social sciences; decision-making; data analyst; filtering; framing
Show Figures

Figure 1

MDPI and ACS Style

Arnaboldi, M. The Missing Variable in Big Data for Social Sciences: The Decision-Maker. Sustainability 2018, 10, 3415.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop