scholarly journals COPING WITH THE DYNAMICS OF URBAN SUSTAINABILITY: POSITIONING URBAN EXPERIMENTATION PLATFORMS AS TOOLS FOR POLICY MAKING

2021 ◽  
Vol XLVI-4/W1-2021 ◽  
pp. 91-96
Author(s):  
S.-V. Rehm ◽  
S. McLoughlin ◽  
G. Maccani
Keyword(s):  
Large Scale ◽  
Urban Governance ◽  
Collective Intelligence ◽  
Urban Sustainability ◽  
Transformation Process ◽  
Organizational Models ◽  
Digital Platforms ◽  
Policy Interventions ◽  
Policy Measures ◽  
Relevant Factors

Abstract. This research considers the creation of resilient organizational models of urban governance to foster urban sustainability. Building on large-scale urban experimentation initiatives, we identify relevant factors in establishing urban experimentation with the help of digital platforms as a means to support such resilient organizational models. Our findings suggest that digital platforms help establish urban experimentation platforms (UXPs) as a core means to innovate towards urban sustainability. UXPs utilize digital platforms to coordinate policy measures and stimulate collective intelligence in order to reach a sustained local socio-technical transformation process. Based on these empirical findings, we use a systems lens to decompose urban experimentation into interconnected sub-systems and then describe some characteristics of their dynamic interaction. Our goal is to develop a System Dynamics model and simulations to support urban public authority decision makers in formulating and implementing policy interventions towards urban sustainability.

scholarly journals Experimentation Platforms as Bridges to Urban Sustainability

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 569-587
Author(s):  
Sven-Volker Rehm ◽  
Shane McLoughlin ◽  
Giovanni Maccani
Keyword(s):  
Case Studies ◽  
Urban Governance ◽  
Design Research ◽  
Participant Observation ◽  
Innovation Process ◽  
Urban Sustainability ◽  
Urban Ecosystem ◽  
Future Research ◽  
Organizational Models ◽  
Multiple Case

Despite immense efforts to realize diverse visions of the ‘smart city,’ municipalities still face manifold uncertainties of how governance and the tools of governance can best support public and regional value creation for achieving urban sustainability. To this end, Urban Living Labs have become a known enabling mechanism. In this paper, we extend the lab idea and formulate the concept of Urban Experimentation Platform that focuses on developing urban innovation ecosystems for urban sustainability. We use action design research and participant observation across multiple case studies enacting Urban Experimentation Platforms in order to investigate how the tie-in between governance and the local lab’s innovation process unfolds. Our analysis distills three facets that are instrumental in institutionalizing these platforms as resilient organizational models. With the help of the case studies, we illustrate the three facets, concerning issues of urban ecosystem governance, empowering co-creation, and qualifying local innovation. The facets reinforce the roles of digital instruments and digital capabilities for effective urban governance and platform management. We draw some conclusions for future research and formulate policy recommendations for implementing and operating Urban Experimentation Platforms.

scholarly journals The impact of COVID-19 on households´ income in the EU

2021 ◽  
Author(s):  
Vanda Almeida ◽  
Salvador Barrios ◽  
Michael Christl ◽  
Silvia De Poli ◽  
Alberto Tumino ◽  
...  
Keyword(s):  
Fiscal Policy ◽  
Disposable Income ◽  
Income Loss ◽  
Eu Member States ◽  
Policy Interventions ◽  
Discretionary Fiscal Policy ◽  
Policy Measures ◽  
The One ◽  
The Impact ◽  
The Eu

AbstractThis analysis makes use of economic forecasts for 2020 issued by the European Commission in Autumn 2019 and Spring 2020, and of a counterfactual under a no-policy change assumption, to analyse the impact of the COVID-19 crisis on EU households´ income. Additionally, our analysis assesses the cushioning effect of discretionary fiscal policy measures taken by the EU Member States. We find that the COVID-19 pandemic is likely to affect significantly households’ disposable income in the EU, with lower income households being more severely hit. However, our results show that due to policy intervention, the impact of the crisis is expected to be similar to the one experienced during the 2008–2009 financial crisis. In detail, our results indicate that discretionary fiscal policy measures will play a significant cushioning role, reducing the size of the income loss (from −9.3% to −4.3% for the average equivalised disposable income), its regressivity and mitigating the poverty impact of the pandemic. We conclude that policy interventions are therefore instrumental in cushioning against the impact of the crisis on inequality and poverty.

Learning Management System for Greater Learner Engagement in Higher Education—A Review

2021 ◽  
pp. 234763112110498
Author(s):  
Parimala Veluvali ◽  
Jayesh Surisetti
Keyword(s):  
Higher Education ◽  
Online Education ◽  
Management System ◽  
Large Scale ◽  
Learning Management System ◽  
Critical Role ◽  
Learner Engagement ◽  
Digital Platforms ◽  
Online Mode ◽  
Learning Management

Online education helped resume learning that had come to a momentary and uncertain pause with the onset of COVID-19 pandemic across the globe. Since then, learning in many educational institutions continued through synchronous and asynchronous modes, with teaching being undertaken remotely on digital platforms. In this large-scale migration towards online mode of curriculum delivery induced by the pandemic, the institutional learning management system (LMS) had a critical role to play in ensuring uninterrupted learning and student engagement. By drawing heavily from extant works, learnings from MOOC platforms, observations from the LMS applications in corporate training, the present article synthesis the extant literature on how the effective use of LMS can make the learning process interactive, student centric, catering to the needs of diverse learners in higher education.

scholarly journals The Wiki Learning Project: Wikipedia as an Open Learning Environment

Comunicar ◽  
2016 ◽  
Vol 24 (49) ◽  
pp. 61-69 ◽  
Author(s):  
Paola Ricaurte-Quijano ◽  
Arianna Carli-Álvarez
Keyword(s):  
Learning Environment ◽  
Knowledge Production ◽  
Collective Intelligence ◽  
Mobile Technologies ◽  
Global Learning ◽  
Open Learning ◽  
Global Knowledge ◽  
Educational Models ◽  
Digital Platforms ◽  
Open Learning Environment

Traditional educational models limit learning possibilities to formal and closed environments. However, mobile technologies and digital platforms are changing this paradigm, expanding learning opportunities. Based on the principles of peer knowledge production, we argue that Wikipedia can be used as an open learning environment that serves several purposes: a) it allows the acquisition of basic skills; b) it contributes to collective intelligence; c) it shortens the global knowledge gap; and, d) it enables the creation of global learning networks. The aim of this study is to introduce the process, strategies, and results of the implementation of the Wiki Learning project at a Mexican university, as an open learning model for the use of Wikipedia as a learning tool. This project included a variety of activities, from article production to workshops by and for students and teachers; 115 students and 57 teachers were surveyed to identify their perception about Wikipedia, its use and potential as educational tool. The results showed that, although the majority are Wikipedia users, there is still a lack of knowledge about its functioning, structure and communities, and a negative perception of the Wikipedia. This poses a great challenge to overcome this stigma and recover the value of collective knowledge production, the purpose of the encyclopedia and its place as a relevant product of collective intelligence. Los enfoques predominantes en el sistema educativo tradicional circunscriben las posibilidades de aprendizaje a entornos formales y cerrados. Sin embargo, las tecnologías móviles y plataformas digitales están transformando este paradigma, expandiendo las posibilidades de aprendizaje. A partir de esta condición y en el marco de la producción del conocimiento entre pares, sostenemos que Wikipedia puede ser utilizada como un entorno de aprendizaje abierto que cumple varios propósitos: a) permite adquirir competencias básicas; b) contribuye a la inteligencia colectiva; c) acorta la brecha global de conocimiento; y, d) facilita la construcción de redes globales de aprendizaje. Este estudio de caso tiene como objetivo presentar el proceso, estrategias y resultados del proyecto Wiki Learning, como modelo de aprendizaje abierto a través del uso de Wikipedia en una universidad mexicana. El proyecto abarcó desde la producción de artículos hasta talleres para el desarrollo de capacidades de profesores y estudiantes. Se realizaron encuestas a 57 docentes y 115 alumnos para identificar la percepción acerca de Wikipedia, su uso y posibilidades como herramienta educativa. Los resultados demostraron que a pesar de que todos son usuarios de Wikipedia, existe un desconocimiento general sobre su funcionamiento, estructura y comunidades, además de cierta desconfianza. Se presenta un desafío para romper el estigma y recuperar el valor de la gestión compartida del conocimiento, el propósito de la enciclopedia y su lugar como producto de la inteligencia colectiva.

Government Policy Interventions and Performance of Indian Engineering Industries

2015 ◽  
pp. 138-158
Author(s):  
Rajdeep Singha ◽  
K. Gayithri
Keyword(s):  
Large Scale ◽  
Engineering Industry ◽  
The Other ◽  
Industrial Growth ◽  
Industrial Policies ◽  
Policy Interventions ◽  
Level Data ◽  
Major Transition ◽  
The Government ◽  
And Performance

The Indian industrial policy made a major transition towards liberalization in the mid-1980s with the proponents of liberalization expecting not only a general increase in the efficiency of Indian industry but also improvement terms of innovative performance. Extensive industrial studies, as well as macro-level data, suggest that liberalization in the field of industrial licensing and foreign technological collaborations has resulted in large-scale entry of new firms across different segments of the economy. In this context, this chapter makes an attempt to review the promotion-oriented industrial policies of the Indian Engineering industry and also trace the industrial growth from 1950-51 onwards. It has been observed that there were mainly two breaks (kinked points) during this period, one in 1965-66 and the other in 1984-85. A review of policies suggests that these breaks were associated with major shifts in policies of the government. The study indicates that the first break came through industrial policies of the government with a focus on the heavy industries during the initial phases, while the other break came during 1984-85, which could be attributed to changes in policies from a restrictive one in the mid-'60s and '70s to a liberalized one in this sector in the '80s.

Harnessing Collective Intelligence Through Pattern Mining in Social Computational Systems

2018 ◽  
pp. 91-110
Author(s):  
Gaganmeet Kaur Awal ◽  
K. K. Bharadwaj
Keyword(s):  
Large Scale ◽  
Social Dynamics ◽  
Pattern Mining ◽  
Collective Intelligence ◽  
Social Systems ◽  
Big Data Analytics ◽  
Diverse Range ◽  
Business Applications ◽  
Computational Systems ◽  
The Web

Due to the digital nature of the web, the social web mimics the real-world social dynamics that manifest themselves as data and can be easily mined as patterns, making the web a fertile ground for business and research-oriented analytical applications. Collective intelligence (CI) is a multifaceted field with roots in sociology, biology, and many other disciplines. Various manifestations of CI support the successful existence of large-scale social systems. This chapter gives an overview of the principles of CI and the concept of “wisdom of crowds” and highlights how to maximize the potential of big data analytics for CI. Also, various techniques and approaches have been described that leverage these CI concepts across a diverse range of ever-evolving social systems for commercial business applications like influence mining, expertise discovery, etc.

mMarketing Opportunities for User Collaborative Environments in Smart Cities

2017 ◽  
pp. 1213-1241
Author(s):  
Artemis D. Avgerou ◽  
Despina A. Karayanni ◽  
Yannis C. Stamatiou
Keyword(s):  
Wireless Communications ◽  
Mobile Devices ◽  
Large Scale ◽  
Collective Intelligence ◽  
Personal Information ◽  
Smart Cities ◽  
Mobility Patterns ◽  
Communications Networks ◽  
Pollution Levels ◽  
Commercial Activities

Smart City infrastructures connect people with their devices through wireless communications networks while they offer sensor-based information about the city's status and needs. Connecting people carrying mobile devices equipped with sensors through such an infrastructure leads to the “collective intelligence” or “crowdsourcing” paradigm. This paradigm has been deployed in numerous contexts such as performing large-scale experiments (e.g., monitoring the pollution levels or analyzing mobility patterns of people to derive useful information about rush hours in cities) or gathering and sharing user collected experiences in efforts to increase privacy awareness and personal information protection levels. In this chapter, we will focus on employing this paradigm in the mMarketing/mCommerce domain and discuss how crowdsourcing can create new opportunities for commercial activities as well as expansion of existing ones.

Inequality and Labour Pains

2020 ◽  
pp. 203-219
Author(s):  
Kaushik Basu
Keyword(s):  
Artificial Intelligence ◽  
New Technology ◽  
Economic Inequality ◽  
The State ◽  
Basic Information ◽  
Digital Platforms ◽  
Global Challenge ◽  
Policy Interventions ◽  
The World ◽  
Labour Pains

A topic that has come increasingly into limelight is rising economic inequality in the world and the suffering of the labouring classes associated with the rise of new technology—in particular, artificial intelligence and digital platforms. Not surprisingly, these were topics with which the author had some ample engagement during his years as policymaker and this chapter speaks to this new global challenge. The chapter provides some basic information about the state of inequality and the falling share of labour income, and also suggests policy interventions to mitigate some of these problems.

A Semantic-Driven Adaptive Architecture for Large Scale P2P Networks

2010 ◽  
Vol 2 (4) ◽  
pp. 12-30 ◽  
Author(s):  
Athena Eftychiou ◽  
Bogdan Vrusias ◽  
Nick Antonopoulos
Keyword(s):  
Large Scale ◽  
Network Formation ◽  
Collective Intelligence ◽  
Semantic Knowledge ◽  
Resource Discovery ◽  
Online Information ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Adaptive Architecture

The increasing amount of online information demands effective, scalable, and accurate mechanisms to manage and search this information. Distributed semantic-enabled architectures, which enforce semantic web technologies for resource discovery, could satisfy these requirements. In this paper, a semantic-driven adaptive architecture is presented, which improves existing resource discovery processes. The P2P network is organised in a two-layered super-peer architecture. The network formation of super-peers is a conceptual representation of the network’s knowledge, shaped from the information provided by the nodes using collective intelligence methods. The authors focus on the creation of a dynamic hierarchical semantic-driven P2P topology using the network’s collective intelligence. The unmanageable amounts of data are transformed into a repository of semantic knowledge, transforming the network into an ontology of conceptually related entities of information collected from the resources located by peers. Appropriate experiments have been undertaken through a case study by simulating the proposed architecture and evaluating results.

scholarly journals Connecting the Digital and Physical World: Improving the Robustness of Adversarial Attacks

2019 ◽  
Vol 33 ◽  
pp. 962-969 ◽  
Author(s):  
Steve T.K. Jan ◽  
Joseph Messou ◽  
Yen-Chen Lin ◽  
Jia-Bin Huang ◽  
Gang Wang
Keyword(s):  
Large Scale ◽  
Physical World ◽  
Transformation Process ◽  
Physical Domain ◽  
Learning Models ◽  
Image Translation ◽  
Physical Transformation ◽  
Adversarial Examples ◽  
Core Idea ◽  
High Level

While deep learning models have achieved unprecedented success in various domains, there is also a growing concern of adversarial attacks against related applications. Recent results show that by adding a small amount of perturbations to an image (imperceptible to humans), the resulting adversarial examples can force a classifier to make targeted mistakes. So far, most existing works focus on crafting adversarial examples in the digital domain, while limited efforts have been devoted to understanding the physical domain attacks. In this work, we explore the feasibility of generating robust adversarial examples that remain effective in the physical domain. Our core idea is to use an image-to-image translation network to simulate the digital-to-physical transformation process for generating robust adversarial examples. To validate our method, we conduct a large-scale physical-domain experiment, which involves manually taking more than 3000 physical domain photos. The results show that our method outperforms existing ones by a large margin and demonstrates a high level of robustness and transferability.

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