Big data use in determining competitive position: The case of theme parks in Hong Kong

2021 ◽  
Vol 22 ◽  
pp. 100668
Author(s):  
Tahir Albayrak ◽  
Aslıhan Dursun Cengizci ◽  
Meltem Caber ◽  
Lawrence Hoc Nang Fong
Keyword(s):  
Big Data ◽  
Hong Kong ◽  
Data Use ◽  
Theme Parks ◽  
Competitive Position

Unpacking Big Data in Education. A Research Framework

2017 ◽  
Vol 8 (2) ◽  
pp. 123-137
Author(s):  
Rosanna De Rosa ◽  
Biagio Aragona
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Use ◽  
Digital Tools ◽  
Policy Cycle ◽  
Core Element ◽  
Technological Revolution ◽  
Research Framework ◽  
Scarce Resources ◽  
Decision Making Processes

Abstract The use of big data represents a valuable way to inspire decision-making in a time of scarce resources. The technological revolution is in fact enabling governments to use a great variety of digital tools and data to manage all phases of the policy cycle process, becoming a core element for e-governance applications and techniques. However, research is seemingly not yet aligned yet with the hybrid environment that both public policies and politics are moving in, while the actors (old and new) and the decision-making processes themselves, in their searching for automation and objectivity, risk being overshadowed. Taking the case of Higher Education, this article proposes a research framework for big-data use to prompt the reflection on the power of “evidence” in decision making; to question and contextualize such evidences in a multimodal and integrated scenario, and to understand the challenges that data will pose to education both in terms of unforeseen and hidden effects.

On meeting students where they are: Teacher judgment and the use of data in higher education

2017 ◽  
Vol 15 (3) ◽  
pp. 321-338 ◽  
Author(s):  
Gina Schouten
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Big Data ◽  
Data Use ◽  
Statistical Information ◽  
Educational Context ◽  
Ongoing Debate ◽  
Moral Hazards ◽  
Use Of Data ◽  
Legal Context

It is treated as a truism that teaching well requires ‘meeting students where they are’. Data enable us to know better where that is. Data can improve instructional practice by informing predictions about which pedagogies will be most successful for which students, and it can improve advising practice by informing predictions about which students are likely to thrive on which pathways moving forward. But moral hazards lurk, and these have been highlighted especially in response to the burgeoning use of new data mining technologies to produce ‘big data’. This article explores the ethics of data use in higher education. I consider the ethics of aggregate data as a tool for meeting students where they are, comparing it to an ongoing debate about the use of statistics in the legal context. The comparison generates two important insights: First, even the most viable moral concerns about using statistical information in the educational context are not deal-breakers: Those concerns should lead us to exercise careful judgment in the use of statistical information but do not justify eschewing that information altogether. Second, surprisingly, those viable moral concerns show big data to have a moral advantage over traditional little data, suggesting that some of the resistance to the use of big data in education is either unfounded or at least needs to be balanced against the moral advantages big data offer.

scholarly journals The Road to Big Data Standardisation

2021 ◽  
pp. 333-354
Author(s):  
Ray Walshe
Keyword(s):  
Big Data ◽  
Data Use ◽  
Single Market ◽  
Use Cases ◽  
Current Status ◽  
Future Trends ◽  
The Road ◽  
Development Organizations ◽  
European Standards ◽  
The Eu

AbstractThis chapter covers the critical topic of standards within the area of big data. Starting with an overview of standardisation as a means for achieving interoperability, the chapter moves on to identify the European Standards Development Organizations that contribute to the European Commission’s plan for the Digital Single Market. The author goes on to describe, through use cases, exemplar big data challenges, demonstrates the need for standardisation and finally identifies the critical big data use cases where standards can add value. The chapter provides an overview of the key standardisation activities within the EU and the current status of international standardisation efforts. Finally, the chapter closes with future trends for big data standardisation.

scholarly journals Viral Data

2020 ◽  
Vol 7 (2) ◽  
pp. 205395172097100
Author(s):  
Agnieszka Leszczynski ◽  
Matthew Zook
Keyword(s):  
Big Data ◽  
Hong Kong ◽  
Data Analytics ◽  
Data Driven ◽  
Tracking Data ◽  
Conspiracy Theories ◽  
Viral Spread ◽  
Data Practices ◽  
Historical Moment

We are experiencing a historical moment characterized by unprecedented conditions of virality: a viral pandemic, the viral diffusion of misinformation and conspiracy theories, the viral momentum of ongoing Hong Kong protests, and the viral spread of #BlackLivesMatter demonstrations and related efforts to defund policing. These co-articulations of crises, traumas, and virality both implicate and are implicated by big data practices occurring in a present that is pervasively mediated by data materialities, deeply rooted dataist ideologies that entrench processes of datafication as granting objective access to truth and attendant practices of tracking, data analytics, algorithmic prediction, and data-driven targeting of individuals and communities. This collection of papers explores how data (and their absences) is figuring in the making of the discourses, lived realities, and systemic inequalities of the uneven impacts of the coronavirus pandemic.

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