Transaction Cost Analysis of PPP Risk Share

PPP (Public Private Partnerships) is a new operation mode of infrastructure projects, which usually undergo long periods and have various kinds of risks in technology, market, politics, policy, finance, society, natural conditions and cooperation. So the government and the private agency should establish the risk-sharing mechanism to ensure the successful implementation of the project. As an important branch of the new institutional economics, transaction cost economics and its analysis method have been proved to be beneficial to the proper allocation of risks between the two parts in PPP projects and the improvement of operation efficiency of PPP risk-sharing mechanism. This paper analyzed the transaction cost of the projects risk-sharing method and the both risk carriers. It pointed out that the risk-sharing method of PPP projects not only reflected the spirit of cooperation between public sector and private agency, but also minimized the total transaction cost of the risk sharing mechanism itself. Meanwhile, the risk takers had to strike a balance between the beforehand cost and the afterwards cost so as to control the cost of risk management. The paper finally suggested three ways which might be useful to reduce the transaction cost: to choose appropriate type of contract of PPP risk-sharing mechanism, to prevent information asymmetry and to establish mutual trust between the two participants.

Creative Commons : fair to share?

This article explores new the realities of the permissions culture and “all rights reserved copyright” in the networked environment and poses the question: why is lending a copy of a book sharing but emailing a PDF of it piracy? It explores new approaches to publishing and distribution of books by highlighting two books in the Aduki Independent Press catalogue. It was modeled on a presentation delivered by Elliott Bledsoe at the Changing Climates in Arts Publishing forum run by Artlink and the Copyright Agency Limited in Adelaide, Australia on 9 May 2009 and in Sydney, Australia on 27 June 2009.

Competitiveness factors : a study of the real estate market in China

The execution of 'macro-adjustment' policies by the central government to cool down the overheated real estate market in the past few years has created an unfavourable operating environment for real estate developers in Mainland China. Developers need to rethink their business model and create a new form of competitive advantage in order to survive. Despite this, research into the factors that influence the competitiveness of the real estate market in China has been limited. Therefore, a survey of 58 real estate actitioners, experts and academics in China was conducted to probe opinion on the factors that influence competitiveness in real estate firms in China. Survey results suggest that the developer's financial competency, market coverage and management competencies are vital to its competitiveness. Findings also highlight the importance of industry ecognition/award, share in different types of property sales/development projects, profit after tax, growth rate of their securities price, and diversification of R&D in reflecting the competitiveness of real estate developers in China. The findings provide an insight into the factors that influence competitiveness in China's real estate market and also assist practitioners to formulate competitiveness improvement strategies.

An effective approach to verbose queries using a limited dependencies language model

Intuitively, any `bag of words' approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distri- butions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document's initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur's search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.

Determining the informational, navigational and transactional intent of web queries

In this paper, we define and present a comprehensive classification of user intent for Web searching. The classification consists of three hierarchical levels of informational, navigational, and transactional intent. After deriving attributes of each, we then developed a software application that automatically classified queries using a Web search engine log of over a million and a half queries submitted by several hundred thousand users. Our findings show that more than 80% of Web queries are informational in nature, with about 10% each being navigational and transactional. In order to validate the accuracy of our algorithm, we manually coded 400 queries and compared the results from this manual classification to the results determined by the automated method. This comparison showed that the automatic classification has an accuracy of 74%. Of the remaining 25% of the queries, the user intent is vague or multi-faceted, pointing to the need for probabilistic classification. We discuss how search engines can use knowledge of user intent to provide more targeted and relevant results in Web searching.

Web searching and Σ2 queries

In the terminology of Logic programming, current search engines answer Sigma1 queries (formulas of the form where is a boolean combination of attributes). Such a query is determined by a particular sequence of keywords input by a user. In order to give more control to users, search engines will have to tackle more expressive queries, namely, Sigma2 queries (formulas of the form ). The purpose of the talk is to examine which directions could be explored in order to move towards more expressive languages, more powerful search engines, and the benefits that users should expect.

Delegation in predicate encryption supporting disjunctive queries

Predicate encryption has an advantage over traditional public-key or identity-based encryption, since predicate encryption systems provide more flexible control over access to encrypted data. We focus on delegation capabilities in predicate systems. More specifically, we investigate delegatable encryption systems supporting disjunctive predicate evaluations. We present formal security definitions of delegatable predicate encryption and provide the first delegatable predicate encryption scheme which supports disjunctive predicate evaluations in the public-key setting. We analyze the security of the proposed system and give a security proof. In addition, we present a delegatable predicate encryption in the symmetric-key setting and discuss the related security issues.