Creating new tech entrepreneurs with digital platforms: Meta-organizations for shared value in data-driven retail ecosystems

2022 ◽  
Vol 175 ◽  
pp. 121392
Author(s):  
Sandro Battisti ◽  
Nivedita Agarwal ◽  
Alexander Brem
Keyword(s):  
Data Driven ◽  
Shared Value ◽  
Digital Platforms

scholarly journals New concepts, different approaches: tackling e-visibility in research project websites

2020 ◽  
Vol 15 (1) ◽  
pp. 83
Author(s):  
Rosa Lorés-Sanz ◽  
Isabel Herrando-Rodrigo
Keyword(s):  
Research Output ◽  
Data Driven ◽  
Discursive Practices ◽  
Research Project ◽  
Privileged Access ◽  
Digital Platforms ◽  
New Concepts ◽  
Scientific Context ◽  
The Web ◽  
International Research Project

<p>In the last few years, the web has become a privileged access platform for knowledge for an increasingly globalized society. Thus, digital platforms are currently used by researchers to strengthen the visibility of their research output as well as their own. In this study we explore the concept of e-visibility as a key notion in the current digital discursive practices within the scientific context. For such purposes we have focused on international research project websites as instances of such practices.The analysis undertaken is data-driven and has revealed the existence of various entities which are made visible by means of a combination of lexicogrammatical devices together with other modes afforded by the digital platforms. Results also show that there are various types of e-visibility emerging from the combination of the entities and the lexicogrammatical and visual resources used to make them visible.</p>

scholarly journals Data-driven urbanism, digital platforms, and the planning of MaaS in times of deep uncertainty: What does it mean for CAVs?

2021 ◽  
pp. 441-470
Author(s):  
Ian Banerjee ◽  
Peraphan Jittrapirom ◽  
Jens S. Dangschat
Keyword(s):  
Critical Review ◽  
Data Driven ◽  
Complex Relationship ◽  
Automated Vehicles ◽  
Deep Uncertainty ◽  
Ongoing Debate ◽  
Digital Platforms ◽  
Governance Models

ZusammenfassungThis paper offers a critical review of three coevolving socio-technical paradigms: (a) “data-driven urbanism,” (b) digital platforms, and (c) “Mobility-as-a-Service” (MaaS). It explores the complex relationship unfolding between data-driven cities and digital platforms, while drawing on MaaS as a case to discuss the challenges of implementing mobility services via digital platforms. Inferences are drawn from the ongoing debate accompanying these three paradigms to identify potential criteria for the design of socially accountable governance models for the deployment of connected and automated vehicles (CAVs).

The technological performance of populism

2018 ◽  
Vol 21 (2) ◽  
pp. 376-397 ◽  
Author(s):  
Jessica Baldwin-Philippi
Keyword(s):  
Mobile Apps ◽  
Data Driven ◽  
Campaign Strategies ◽  
Media Environment ◽  
Digital Platforms ◽  
Technological Performance ◽  
The People ◽  
Contemporary Media ◽  
Do So

This article investigates the Trump campaign’s strategic use of digital platforms and their affordances and norms that contribute to a technological performance of populism. To do so, I build on theories of populism as a performance, rather than a set of identifiable qualities, and make a theoretical intervention calling for the need to add a material and technological focus to how scholars approach the concept in our contemporary media environment. This article presents a model for understanding populist affordances as those that center “the people” to various degrees, and applies that model in a case study of how campaigns in the 2016 US presidential race engaged in a technological performance of populism across a variety of platforms, including email, Twitter, Instagram, Facebook, and campaign-created mobile apps. Central to this analysis are campaign strategies of controlled interactivity, amateurism, participatory/user-generated content, and data-driven campaigning.

scholarly journals Big Data-Driven Value Chains and Digital Platforms: From Value Co-creation to Monetization

2017 ◽  
pp. 355-372 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Alberto Larocca ◽  
Michele Marconi
Keyword(s):  
Big Data ◽  
Data Driven ◽  
Value Chains ◽  
Digital Platforms

scholarly journals Social media, context collapse and the future of data-driven populism

2020 ◽  
Author(s):  
Frederic Guerrero-Solé ◽  
Sara Suárez-Gonzalo ◽  
Cristòfol Rovira ◽  
Lluís Codina
Keyword(s):  
Social Media ◽  
Political Communication ◽  
Data Driven ◽  
Digital Networks ◽  
Time Data ◽  
Theoretical Understanding ◽  
Digital Platforms ◽  
The People ◽  
Communicative Strategies ◽  
Ideal Situation

During the last decades populism has become a mainstream ideology in Western democracies (Mudde, 2004; 2016). At the same time, the popularisation of digital platforms has facilitated the process of political communication while social networks have become one of the preferred communicative tools for political populists to spread their messages. Drawing on the idea that computational technologies allow a particular performance of populism (Baldwin-Philippi, 2019), this paper aims to foster a better theoretical understanding of how innovation in communication technologies contribute to the success of populism. It is argued that the characteristics of populism (a focus on ‘the people’, technological savviness and chameleonism) allow it to overcome most of the obstacles put in place by digital networks. In particular, populism is in an ideal situation to deal with the phenomena of context collapse in social media (Boyd; Marwick, 2011). Finally, it is argued that in the era of personalized politics (Bennett, 2012), populists can make use of real-time data-driven techniques to develop successful communicative strategies addressed to mass audiences in order to construct the populist self in the image and likeness of the people. This form of populism is called data-driven populism.

Putting trust into antitrust? Competition policy and data-driven platforms

2021 ◽  
pp. 026732312110283
Author(s):  
Stefan Larsson
Keyword(s):  
Competition Policy ◽  
Personal Data ◽  
Competition Law ◽  
Data Driven ◽  
Data Handling ◽  
Special Issue ◽  
Digital Platforms ◽  
Platform Governance ◽  
Consumer Autonomy ◽  
The Relationship

Anti-competitive notions, it seems, are increasingly informing the critical debate on a data-driven economy organised into scalable digital platforms. Issues of market definitions, how to value personal data on multisided platforms, and how to detect and regulate misuses of dominant positions have become key nomenclature on the battlefield of addressing fairness in our contemporary digital societies. This article looks at the central themes for this special issue on governing trust in European platform societies through the lens of contemporary developments in the field of competition law. Three main questions are addressed: (1) To what extent are the platforms’ own abilities to govern their infrastructures, that is, to be de facto regulators over both human behaviour and market circumstances, a challenge for contemporary competition regulation? (2) In what way is the collection, aggregation, or handling of consumers’ data of relevance for competition? (3) How can the particular European challenges of governing US-based digital platforms more broadly be understood in terms of the relationship between transparency and public trust? Of particular relevance – and challenge – here are the platforms’ abilities to govern their infrastructures, albeit through automated moderation, pricing or scalable data handling. It is argued that this aspect of coded, and possibly autonomously adapting, intra-platform governance, poses significant anti-competitive challenges for supervisory authorities, with possible negative implications for consumer autonomy and wellbeing as well as platform-dependent other companies.

Big Data-Driven Value Chains and Digital Platforms: From Value Co-Creation to Monetization

2017 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Alberto Larocca ◽  
Michele Marconi
Keyword(s):  
Big Data ◽  
Data Driven ◽  
Value Chains ◽  
Digital Platforms

scholarly journals Data and E-commerce: An Economic Relationship

2021 ◽  
Vol 12 (1) ◽  
pp. 33-44
Author(s):  
Libor Klimek ◽  
Rastislav Funta
Keyword(s):  
Business Model ◽  
Legal Framework ◽  
Data Driven ◽  
Digital Platforms ◽  
Use Of Data ◽  
Online Platforms ◽  
Success Model ◽  
Economic Relationship ◽  
Almost All ◽  
Platform Economy

Abstract In almost all sectors, online services play a much larger role than a few years ago. Data-driven platform models combine an ever greater degree of market power. The associated concentration effect leads to the displacement of medium-sized companies from the market. When looking at the large platforms of this new digital economy their success model is based almost exclusively on generating data and extracting economically useful information from this data. In relation to trading platforms, the use of data serves among other things to increase efficiency. The so-called data sharing offers numerous advantages that can be leveraged in connection with e-commerce platforms. Due to this, we will first take a closer look at e-commerce and the special economic characteristics of the business model of digital platforms (especially Amazon). The next chapter discusses the current legal framework and focus on the antitrust claims of retailers against online platforms. Then, we will deal with the legal-political approaches to the digital platform economy. The study concludes with various options for action which can be derived from the legal and economic explanations outlined in the previous chapters.

scholarly journals Be Careful What You Wish For! Learning Analytics and the Emergence of Data-Driven Practices in Higher Education

2021 ◽  
pp. 203-226
Author(s):  
Teresa Cerratto Pargman ◽  
Cormac McGrath
Keyword(s):  
Higher Education ◽  
Critical Pedagogy ◽  
Learning Analytics ◽  
Data Driven ◽  
Valuable Insight ◽  
Educational Values ◽  
Evidence Based Practices ◽  
Digital Platforms ◽  
Context Sensitive

With the growing digitalization of the education sector, the availability of significant amounts of data, “big data,” creates possibilities for the use of artificial intelligence technologies to gain valuable insight into how students learn in higher education. Learning analytics technologies are examples of how deep learning algorithms can identify patterns in data and incorporate this “knowledge” into a model that is eventually integrated into the digital platforms used for interacting with students. This chapter introduces learning analytics as an emerging sociotechnical phenomenon in higher education. We situate the promises and expectations associated with learning analytics technologies, map their ties to emerging data-driven practices, and unpack the ethical concerns that are related to such practices via examples.Following this, we discuss three insights that we hope will provoke discussions among educators, researchers, and practitioners in higher education: (1) educational data-driven practices are highly context sensitive, (2) educational data-driven practices are not synonymous with evidence-based practices, and (3) innovative educational data-driven practices are not sustainable per se. This chapter calls for debating the role of emerging data-driven practices in higher education in relation to academic freedom and educational values embedded in critical pedagogy.

scholarly journals Competition Law in Asia: The Interplay of Power Dynamics in the Digital Market

Lentera Hukum ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 295
Author(s):  
Ankit Srivastava ◽  
Aditi Richa Tiwary
Keyword(s):  
Data Privacy ◽  
Primary Source ◽  
Competition Law ◽  
Digital Economy ◽  
Data Driven ◽  
Power Dynamics ◽  
Digital Platforms ◽  
Cross Border ◽  
Competition Laws ◽  
Evaluation Parameters

The digital economy and multi-faceted markets have significantly contributed to the efficacy of most transactions governing modern humankind. Digital platforms have become an irreplaceable cross-border asset that has acclimatized with technological advancements. However, there is obscurity in the methods of accommodation of digital economy in competition laws of most jurisdictions globally. Consequently, there are ascertainable issues in competition laws of such jurisdictions. Such issues remain unaddressed due to the absence of evaluation parameters of digital platforms in the conventional market system and culminate into an Implicit and undetected abuse of dominance. This study used the doctrinal method by highlighting the distinctness of contemporary digital markets and their consequential issues. This study explicated the issues in the competition that need to be independently addressed, considering the intricacies of digital platforms. The presence of non-price factors, multi-faceted markets, and data-driven networks being the primary source of such novel issues have been particularly explicated. The established premise was substantiated by way of case studies of major events involving factors such as predation, deep discounting, and data privacy. Elucidation of the competition system in most jurisdictions in Asia and the accommodation of digital platforms in the same was also sufficiently enunciated to present a holistic insight to the established premise. Finally, the authors suggested ways to sufficiently address the issues arising from the distinctness of digital platforms, thereby giving rise to a dynamic and all-inclusive competition. KEYWORDS: Digital Markets, Competition Law, Data Privacy.

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