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 & Context (language use). The organization has 5658 authors who have published 11562 publications receiving 295257 citations.

Determinants of consumer engagement in electronic word-of-mouth in social networking sites

Abstract: As more and more marketers incorporate social media as an integral part of the promotional mix, rigorous investigation of the determinants that impact consumers’ engagement in eWOM via social networks is becoming critical. Given the social and communal characteristics of social networking sites (SNSs) such as Facebook, MySpace and Friendster, this study examines how social relationship factors relate to eWOM transmitted via online social websites. Specifically, a conceptual model that identifies tie strength, homophily, trust, normative and informational interpersonal influence as an important antecedent to eWOM behaviour in SNSs was developed and tested. The results confirm that tie strength, trust, normative and informational influence are positively associated with users’ overall eWOM behaviour, whereas a negative relationship was found with regard to homophily. This study suggests that product-focused eWOM in SNSs is a unique phenomenon with important social implications. The implications for research...

Organization Strategy and Structural Differences for Radical Versus Incremental Innovation

Abstract: The purpose of this study was to test a model of the organizational innovation process that suggests that the strategy-structure causal sequence is differentiated by radical versus incremental innovation. That is, unique strategy and structure will be required for radical innovation, especially process adoption, while more traditional strategy and structure arrangements tend to support new product introduction and incremental process adoption. This differentiated theory is strongly supported by data from the food processing industry. Specifically, radical process and packaging adoption are significantly promoted by an aggressive technology policy and the concentration of technical specialists. Incremental process adoption and new product introduction tends to be promoted in large, complex, decentralized organizations that have market dominated growth strategies. Findings also suggest that more traditional structural arrangements might be used for radical change initiation if the general tendencies that occur in these dimensions as a result of increasing size can be delayed, briefly modified, or if the organization can be partitioned structurally for radical vs. incremental innovation. In particular, centralization of decision making appears to be necessary for radical process adoption along with the movement away from complexity toward more organizational generalists. This suggests that a greater support of top managers in the innovation process is necessary to initiate and sustain radical departures from the past for that organization.

Automatic personalization based on Web usage mining

Abstract: The ease and speed with which business transactions can be carried out over the Web have been a key driving force in the rapid growth of electronic commerce. Business-to-business e-commerce is the focus of much attention today, mainly due to its huge volume. While there are certainly gains to be made in this arena, most of it is the implementation of much more efficient supply management, payments, etc. On the other hand, e-commerce activity that involves the end user is undergoing a significant revolution. The ability to track users’ browsing behavior down to individual mouse clicks has brought the vendor and end customer closer than ever before. It is now possible for a vendor to personalize his product message for individual customers at a massive scale, a phenomenon that is being referred to as mass customization.

Context-Aware Recommender Systems

Abstract: Context-aware recommender systems (CARS) generate more relevant recommendations by adapting them to the specific contextual situation of the user. This article explores how contextual information can be used to create more intelligent and useful recommender systems. It provides an overview of the multifaceted notion of context, discusses several approaches for incorporating contextual information in recommendation process, and illustrates the usage of such approaches in several application areas where different types of contexts are exploited. The article concludes by discussing the challenges and future research directions for context-aware recommender systems.

Hybrid web recommender systems

Abstract: Adaptive web sites may offer automated recommendations generated through any number of well-studied techniques including collaborative, content-based and knowledge-based recommendation. Each of these techniques has its own strengths and weaknesses. In search of better performance, researchers have combined recommendation techniques to build hybrid recommender systems. This chapter surveys the space of two-part hybrid recommender systems, comparing four different recommendation techniques and seven different hybridization strategies. Implementations of 41 hybrids including some novel combinations are examined and compared. The study finds that cascade and augmented hybrids work well, especially when combining two components of differing strengths.