It is well understood that "good institutions" are essential for good governance. But even institutions that follow similar designs vary significantly with regard to performance across countries and even across regions within the same country. Following China's abolishment of the Commune system to accommodate market-oriented reforms in the 1980s, decentralized, grassroots democracy was introduced in rural China in order to improve the quality of local governance. In this book, Jie Lu looks at variance among local governance institutions in China to examine under what conditions indigenously cultivated institutions or externally imposed institutions are able to succeed, particularly under pressures of economic modernization. Lu argues that any governance institution can perform effectively as long as it can produce collective action and accountability, but the relative effectiveness of institutions is contingent upon the social environment in which they are embedded. When economic conditions prompt outward migration, social environments are reshaped such that rules-based formal institutions will trump relation-based indigenous forms. In identifying the optimal social conditions for the effective performance of different governance institutions and theorizing the effects of social change on these institutions, Lu deepens understanding of how institutions, particularly in developing countries, change, and under what conditions institutional modernization or engineering may succeed or fail.

Understandings of Democracy examines why democracy is in trouble in today's world, even when most people profess to love democracy. Jie Lu and Yun-han Chu argue that people hold distinct understandings of democracy, and popular understandings of democracy have critically shaped how citizens respond to authoritarian or populist practices in contemporary politics. Using large-scale comparative surveys and survey experiments from seventy-two societies and a national survey in the United States, this book captures how people respond when presented with the tradeoffs between the intrinsic and instrumental values of democracy, as well as the attitudinal and behavioral implications of such responses.

This book deals with contemporary Chinese literature and literary culture, especially in regard to the impact of globalisation, and analyses the innovative narrative structure of Chinese experimental writings (from the mid 1980s to the 1990s) as both reflecting and contributing to broader changes in the consciousness of time. It focuses on the relationship between fictional narrative form and contemporary Chinese post-historical experiences prompted by political, sociocultural and socioeconomic changes as well as global influences.

Cognition-driven decision support system (DSS) has been recognized as a paradigm in the research and development of business intelligence (BI). Cognitive decision support aims to help managers in their decision making from human cognitive aspects, such as thinking, sensing, understanding and predicting, and fully reuse their experience. Among these cognitive aspects, decision makers’ situation awareness (SA) and mental models are considered to be two important prerequisites for decision making, particularly in ill-structured and dynamic decision situations with uncertainties, time pressure and high personal stake. In today’s business domain, decision making is becoming increasingly complex. To make a successful decision, managers’ SA about their business environments becomes a critical factor. This book presents theoretical models as well practical techniques of cognitiondriven DSS. It first introduces some important concepts of cognition orientation in decision making process and some techniques in related research areas including DSS, data warehouse and BI, offering readers a preliminary for moving forward in this book. It then proposes a cognition-driven decision process (CDDP) model which incorporates SA and experience (mental models) as its central components. The goal of the CDDP model is to facilitate cognitive decision support to managers on the basis of BI systems. It also presents relevant techniques developed to support the implementation of the CDDP model in a BI environment. Key issues addressed of a typical business decision cycle in the CDDP model include: natural language interface for a manager’s SA input, extraction of SA semantics, construction of data warehouse queries based on the manger’s SA and experience, situation information retrieval from data warehouse, how the manager perceives situation information and update SA, how the manager’s SA leads to a final decision. Finally, a cognition-driven DSS, FACETS, and two illustrative applications of this system are discussed.

Recommender systems provide users (businesses or individuals) with personalized online recommendations of products or information, to address the problem of information overload and improve personalized services. Recent successful applications of recommender systems are providing solutions to transform online services for e-government, e-business, e-commerce, e-shopping, e-library, e-learning, e-tourism, and more.This unique compendium not only describes theoretical research but also reports on new application developments, prototypes, and real-world case studies of recommender systems. The comprehensive volume provides readers with a timely snapshot of how new recommendation methods and algorithms can overcome challenging issues. Furthermore, the monograph systematically presents three dimensions of recommender systems — basic recommender system concepts, advanced recommender system methods, and real-world recommender system applications.By providing state-of-the-art knowledge, this excellent reference text will immensely benefit researchers, managers, and professionals in business, government, and education to understand the concepts, methods, algorithms and application developments in recommender systems.

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.

Business organizations and governments are nowadays developing and providing internet based electronic services (e-services) featuring various intelligent functions. This book offers a thorough introduction and systematic overview of the new field e-service intelligence. It covers the state-of-the-art of e-service intelligence including both theorems and applications, and a broad range of topics are discussed.

This book proposes a set of models to describe fuzzy multi-objective decision making (MODM), fuzzy multi-criteria decision making (MCDM), fuzzy group decision making (GDM) and fuzzy multi-objective group decision-making problems, respectively. It also gives a set of related methods (including algorithms) to solve these problems. One distinguishing feature of this book is that it provides two decision support systems software for readers to apply these proposed methods. A set of real-world applications and some new directions in this area are then described to further instruct readers how to use these methods and software in their practice.