658 resultados para Collaborative Economy
Resumo:
Tagging provides support for retrieval and categorization of online content depending on users' tag choice. A number of models of tagging behaviour have been proposed to identify factors that are considered to affect taggers, such as users' tagging history. In this paper, we use Semiotics Analysis and Activity theory, to study the effect the system designer has over tagging behaviour. The framework we use shows the components that comprise the tagging system and how they interact together to direct tagging behaviour. We analysed two collaborative tagging systems: CiteULike and Delicious by studying their components by applying our framework. Using datasets from both systems, we found that 35% of CiteULike users did not provide tags compared to only 0.1% of Delicious users. This was directly linked to the type of tools used by the system designer to support tagging.
Resumo:
Web service is one of the most fundamental technologies in implementing service oriented architecture (SOA) based applications. One essential challenge related to web service is to find suitable candidates with regard to web service consumer’s requests, which is normally called web service discovery. During a web service discovery protocol, it is expected that the consumer will find it hard to distinguish which ones are more suitable in the retrieval set, thereby making selection of web services a critical task. In this paper, inspired by the idea that the service composition pattern is significant hint for service selection, a personal profiling mechanism is proposed to improve ranking and recommendation performance. Since service selection is highly dependent on the composition process, personal knowledge is accumulated from previous service composition process and shared via collaborative filtering where a set of users with similar interest will be firstly identified. Afterwards a web service re-ranking mechanism is employed for personalised recommendation. Experimental studies are conduced and analysed to demonstrate the promising potential of this research.
Resumo:
It is estimated that globally over 2 billion people do not have a bank account, with many more in the developed and developing worlds ‘under-banked’, meaning they have limited access to financial services. Reaching the unbanked and underbanked with appropriate financial services is widely recognised as critical for future global economic growth and prosperity. Drawing upon multidimensional understandings of poverty, and framed by literature on poverty pools, traps and cycles, this paper explores the use of financial products and services in the developing world and critically reflects on their potential role in poverty alleviation and wider sustainable development. Discussions are illustrated with reference to qualitative empirical research undertaken in East and Southern Africa, and a sense-making of the lived financial experiences of low income individuals, households and communities.
Resumo:
Purpose The purpose of this paper is to assess and highlight the approach taken towards the legal control of illicit money laundering taken in the Republic of Kazakhstan, in particular, the role played by an amnesty on the legalisation of illicit funds. This is particularly important as a basis for a wider discussion about the proper limits of the “criminalising” approaches commonly taken in anti-money laundering regulations. Design/methodology/approach The discussion and evaluation in the paper is based upon a conceptual analysis of the money laundering regime in Kazakhstan, in particular, the legal framework and policies of implementation adopted. Findings The paper demonstrates that the problems that are posed by the shadow economy in post-Soviet transition societies can make the blanket criminalisation of money laundering a self-defeating approach, unless accompanied by measures which allow for the achievement of “market-constituting” effects. Research limitations/implications The paper draws on experience and practice in one jurisdiction only (Kazakhstan); it also limits its focus to one particular example of a money laundering amnesty policy. Both of these limitations, therefore, suggest avenues for further comparative research. Originality/value The paper’s conclusions about the interactions between the shadow economies of transitional societies and the global anti-money laundering agenda have wider application in assessments of international law in this area.
Resumo:
This paper considers the longer-term viability of the internationalization and success of Indian multinational enterprises (MNEs). We apply the ‘dual economy’ concept (Lewis, Manch Sch 22(2):139–191, 1954) to reconcile the contradictions of the typical emerging economy, where a ‘modern’ knowledge-intensive economy exists alongside a ‘traditional’ resource-intensive economy. Each type of economy generates firms with different types of ownership advantages, and hence different types of MNEs and internationalisation patterns. We also highlight the vulnerabilities of a growth-by-acquisitions approach. The potential for Indian MNEs to grow requires an understanding of India’s dual economy and the constraints from the home country’s location advantages, particularly those in its knowledge infrastructure.
Resumo:
Green economy has become one of the most fashionable terms in global environmental public policy discussions and forums. Despite this popularity, and its being selected as one of the organizing themes of the United Nations Rio+20 Conference in Brazil, June 2012, its prospects as an effective mobilization tool for global environmental sustainability scholarship and practice remains unclear. A major reason for this is that much like its precursor concepts such as environmental sustainability and sustainable development, green economy is a woolly concept which lends itself to many interpretations. Hence, rather than resolve long-standing controversies, green economy merely reinvigorates existing debates over the visions, actors and policies best suited to secure a more sustainable future for all. In this review article, we aim to fill an important gap in scholarship by suggesting various ways in which green economy may be organized and synthesized as a concept, and especially in terms of its relationship with the idea of social and environmental justice. Accordingly, we offer a systemization of possible interpretations of green economy mapped onto a synthesis of existing typologies of environmental justice. This classification provides the context for future analysis of which, and how, various notions of green economy link with various conceptions of justice.
Resumo:
The creative industries have attracted the attention of academics and policy makers for the complexity surrounding their development, supply-chains and models of production. In particular, many have recognised the difficulty in capturing the role that digital technologies play within the creative industries. Digital technologies are embedded in the production and market structures of the creative industries and are also partially distinct and discernible from it. This paper unfolds the role played by digital technologies focusing on a key aspect of its development: human capital. Using student micro-data collected by the Higher Education Statistical Agency (HESA) in the United Kingdom, we investigate the characteristics and location determinants of digital graduates. The paper deals specifically with understanding whether digital skills in the UK are equally embedded across the creative industries, or are concentrated in other sub-sectors. Furthermore, it explores the role that these graduates play in each sub-sector and their financial rewards. Findings suggest that digital technology graduates tend to concentrate in the software and gaming sub-sector of the creative industries but also are likely to be in embedded creative jobs outside of the creative industries. Although they are more likely to be in full-time employment than part-time or self-employment, they also suffer from a higher level of unemployment.
Resumo:
This paper is an extension of our previous study on pragmatic interoperability assessment for process alignment. In this study, we conduct four case studies in industrial companies and hospitals in order to gather their viewpoints regarding the concerns when condensing process alignment in a collaborative working environment. Used techniques include interview, observation, and documentation. The collected results firstly are summarised into three layers based on our previous developed pragmatic assessment model, and then are transformed into the elements which constitutes the purposed method, and finally based on the summarised results we purpose a method for assessing pragmatic interoperability for process alignment in collaborative working environment. The method contains two parts: one gives all the elements of pragmatic interoperability that should be concerned when considering process alignment in collaborative working environment, and the other one is a supplementary method for dealing with technical concerns.
Resumo:
Currently researchers in the field of personalized recommendations bear little consideration on users' interest differences in resource attributes although resource attribute is usually one of the most important factors in determining user preferences. To solve this problem, the paper builds an evaluation model of user interest based on resource multi-attributes, proposes a modified Pearson-Compatibility multi-attribute group decision-making algorithm, and introduces an algorithm to solve the recommendation problem of k-neighbor similar users. Considering the characteristics of collaborative filtering recommendation, the paper addresses the issues on the preference differences of similar users, incomplete values, and advanced converge of the algorithm. Thus the paper realizes multi-attribute collaborative filtering. Finally, the effectiveness of the algorithm is proved by an experiment of collaborative recommendation among multi-users based on virtual environment. The experimental results show that the algorithm has a high accuracy on predicting target users' attribute preferences and has a strong anti-interference ability on deviation and incomplete values.