Guest Editors’ Introduction

Inf Technol Manag (2009) 10:81 DOI 10.1007/s10799-009-0053-6 INTRODUCTION Guest Editors’ Introduction Kaushal Chari Æ Akhil Kumar Published online: 8 July 2009 Ó Springer Science+Business Media, LLC 2009 This issue contains expanded versions of five papers from the 17th Workshop on Information Technology and Systems (WITS) that was held in Montreal in December 2007. After the workshop authors were invited to submit full versions of their papers for this special issue. Each paper that was finally selected was reviewed by three independent reviewers and went through two rigorous rounds of reviews. The mix of these papers reflects the diversity of topics that were covered at WITS 2007. However, the common feature in these papers is that they all fall broadly in the area of design science research. The first paper by Abbasi and Chen discusses automated techniques for identifying fake escrow web sites with a high degree of success. The second paper by Al-Natour and Cavusoglu proposes dependency diagrams as a way to understand inter-functional and inter-organizational knowledge linkages. They develop a new modeling grammar that enables users to diagram and analyze intra and inter-organizational knowledge flows. In the third paper, Smith, Giraud-Carrier and Purser describe another class of social networks, known as Implicit Affinity Networks (IANs), where links are implicit in the patterns of natural affinities among individuals. They give a mathematical formulation of social capital based on implicit and explicit connections. The focus of the next paper by Hühn, Markl and Bichler is on large-scale distributed transaction processing (DTP) systems. They study the predictive performance of queuing network models for such systems through experiments and show that their models provide a reliable and fast methodology to explore different demand mix scenarios in the real world. In the last paper, Takano, Chen and Masuda propose a novel technique for information retrieval where the vector space is personalized leading to highly accurate retrieval results. They present a method for analyzing and customizing the vector space according to the purposes and interests of a user. The following reviewers provided valuable assistance during the review process and are gratefully acknowledged: Akhilesh Bajaj Kaushik Dutta Zan Huang Vijay Khatri Jeff Nickerson Balaji Padmanabhan Gautam Pant Praveen Pathak Johan Perols Sanjukta Smith Anjana Susarla Yong Tan Catherine Yang Eric Zhang Huimin Zhao We hope you will enjoy reading this issue. K. Chari (&) University of South Florida, Tampa, FL, USA e-mail: A. Kumar Pennsylvania State University, University Park, PA, USA 123  (...truncated)