DePaul University

About: DePaul University is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 5658 authors who have published 11562 publications receiving 295257 citations.

The Efficacy of Third-Party Consultation in Preventing Managerial Escalation of Commitment: The Role of Mental Representations

Abstract: Avoiding continued investment in poorly performing projects is an important function of management control systems. However, prior research suggests that managers fail to use accounting information indicating that a project is performing poorly to discontinue it; that is, they escalate commitment to the project. We perform two experiments to investigate the efficacy of a potential control mechanism, third-party consultation, in preventing managerial escalation of commitment. We hypothesize that the information-processing objective (i.e., purpose) assigned to consultants influences the mental representations they construct to process and store information, which ultimately influences their recommendations regarding the continuation of a poorly performing project. Results suggest that consultants will not construct mental representations amenable to making high-quality project-continuation recommendations unless they are assigned that specific purpose. Results further suggest that applying additional effort likely will not overcome the adverse effects of having inappropriate mental representations when making project-continuation recommendations. An implication of our study is that third-party consultants likely will not prevent managerial escalation of commitment unless consultants have a specific mandate of making a project-continuation recommendation in mind when they encounter relevant accounting information.

Context-Aware Recommendation Based On Review Mining

Abstract: Recommender systems (RS) play an important role in many areas including targeted advertising, personalized marketing and information retrieval. In recent years, the importance of contextual information has attracted many researchers to focus on designing systems that produce personalized recommendations in accordance with available contextual information of users. Comparing with traditional RS which mainly utilize users’ rating history, the context# aware recommender systems (CARS) can result in better performance in various applications. In this paper, we present a context#aware recommender system that extracts contextual information from a textual description of user current situation and use it in combination with user ratings history to compute a utility function over the set of items. The item utility shows how much it is preferable regarding user current context. In our system, the context inference is modeled as a supervised topic#modeling problem in which the set of categories for a contextual attribute constitutes the topic set. As an example application, we used our method to mine hidden contextual data from customers' reviews for hotels and use it to produce context#aware recommendations. Our evaluations suggest that our system can help produce better recommendations in comparison to a standard kNN recommender system.

An Ideological/Cultural Analysis of Political Slogans in Communist China:

Abstract: By employing the frameworks of McGee's discussion on the relationship between ideology and ideographs, Wander's approach to the identification of fact and negation in cultural analysis, and by addressing Arendt's question on the process of indoctrination in totalitarian regimes, this study examines the use of political slogans in Communist China from the early 1960s to the late 1980s. It discusses rhetorical impacts of these political slogans on transforming Chinese ideology from Confucianism to Maoism, and to Deng Xiaoping's pragmatism. The analysis indicates that political slogans are coined to meet the changing need of social conditions as well as the need of authorities to establish control. Moreover, the pervasive use of these political slogans has altered the face of Chinese culture and affected the Chinese thought pattern. The rhetorical strategies and techniques employed by Communist China resemble closely those employed by other totalitarian regimes.

The Role of Emotions in Context-aware Recommendation.

Abstract: Context-aware recommender systems try to adapt to users’ preferences across different contexts and have been proven to provide better predictive performance in a number of domains. Emotion is one of the most popular contextual variables, but few researchers have explored how emotions take effect in recommendations – especially the usage of the emotional variables other than the effectiveness alone. In this paper, we explore the role of emotions in context-aware recommendation algorithms. More specifically, we evaluate two types of popular context-aware recommendation algorithms – context-aware splitting approaches and differential context modeling. We examine predictive performance, and also explore the usage of emotions to discover how emotional features interact with those context-aware recommendation algorithms in the recommendation process.