102 An Empirical Assessment of the Impact of ERP Task-Technology Fit on Decision Quality Arun Madapusi Department of Decision Sciences LeBow College of Business Drexel University 204 Academic Building Philadelphia, PA 19104, USA Phone: 215-895-2130, Email: madapusi@drexel.edu Daniel Cernas Ortiz Department of Management College of Business University of North Texas P.O. Box 305429 Denton, Texas 76203-5429, USA Phone: 940-565-3140, Email: CernasD@unt.edu ABSTRACT In this research study, a model is developed to assess the task-technology fit of ERP enterprise resource planning (ERP) systems and the performance of individual decision makers. The ERP task-technology factors and decision quality measures were identified from a synthesis of literature and adapted for the purposes of this study. Data were collected from the ERP system users in a firm that had deployed an ERP system. The data were analyzed using factor and multiple regression analyses techniques. The results and the implications of the findings are discussed. INTRODUCTION Decision quality has emerged as a critical concern for firms in today‟s uncertain and complex business environments. Over the past decade firms have increasingly used enterprise resource planning (ERP) systems to facilitate and support their decision making needs. Due to the high incidences of ERP deployment delays and failures, most studies have focused on the effective management of the ERP implementation process. There is a paucity of studies that have examined ERP usage issues. In this study, we address the above literature gap by evaluating the link between ERP task-technology fit and decision quality. Past research reveals that alignment between task needs and system functionalities increases the performance impact of information systems (Goodhue, 1995; Goodhue and Thompson, 1995; Goodhue, 1998; Madapusi and Kuo, 2007; Madapusi et al., 2007; Madapusi, 2008). These studies further indicate that user evaluations of task needs and system functionalities provide a conceptual link between user evaluations and individual performance.