714 Construction of Extended Technology Acceptance Model of Electronic Medical Records in Jordan: The Influence of Doctors’ Self-Efficacy and Perceived Behavioral Control Ola Thaseer Khorma a , Fauziah Baharom c , Haslina Mohd b Applied Science Division, College of Arts & Sciences, Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia a,b,c,d,e ola_khorma@hotmail.com a , fauziah@uum.edu.my b , haslina@uum.edu.my a , phone: 04-9284701, fax: 6049284753 ABSTRACT The implementation of Electronic Medical Record (EMR) in Jordan public hospitals has started since 2009. The motivation of doing this study is to observe doctors’ acceptance of EMR in Jordanian public hospitals. This study aims at constructing doctors’ acceptance model of EMR using Technology Acceptance Model (TAM) based on individual capabilities. The model will apply TAM as the basic theory and extending Self-Efficacy (SE) and Perceived Behavioral Control (PBC) as two factors of individual characteristics. Initial findings show that the main factors of the model should compose of Perceived Usefulness, Perceived Ease of Use, Behavioral Intention to Use, Self-Efficacy, and Perceived Behavioral Control. The result of the pilot test shows that all factors are reliable with Cronbach Alpa 0.838. The recommendation to the top management of healthcare organization, in order to increase doctors’ acceptance of EMR, that the new deployment of EMR should focus on delivering awareness and continuous training on using EMR among doctors at the early stage of EMR implementation . Keywords Technology Acceptance Model, Perceived Usefulness, and Perceived Ease of Use, Behavioral Intention to Use, Self-Efficacy, Perceived Behavioral Control, and Individual Characteristics. 1.0 INTRODUCTION EMR is defined as “a patient record system which is the set of components that form the mechanism by which patient records are created, used, stored, and retrieved. A patient record system is usually located within a health care provider setting. It includes people, data, rules and procedures, processing and storage devices, and communication and support facilities” (Institute of Medicine (IOM), 1997). EMR offers a lot of benefits such as improving patient safety and quality (Edwards, 2006), reducing medical error (Croll, 2010), and reducing costs of data collection (Thompson, Classen, & Haug, 2007). Despite the obvious benefit of using Information Systems (IS) in an organization, the resistance of IS users is a common problem (Daim, Tarman, & Basoglu, 2008), and healthcare industry is considered as one of the industries that suffer from this problem (Daim et al., 2008). However, EMR adoption has received little attention in the IS literature, thus, there is a need to study this phenomenon (Hennington & Janz, 2007). EMR can enhance the healthcare services' delivery (DesRoches et al., 2008), but it has been slow in becoming part of the participation of healthcare professionals, which has led healthcare organizations not to adopt EMR systems (DesRoches et al., 2008). Therefore, there is a need to study on doctors’ acceptance and the factors that influence the use of EMR. User acceptance and the use of technology have been issues of research for over a decade (Venkatesh, 2000). Dillon and Morris (1996) defined user acceptance as “the obvious willingness within a group to use IT for the tasks it is designed to support”. Moreover, it was found that studies on user acceptance of healthcare systems regarding healthcare managers and professionals’ perceptions have affected the healthcare system implementation’s success (Kijsanayotin et al., 2009). There have been several theoretical models introduced to study user acceptance of IS implementation. Among of them are Theory of Reasoned Action (TRA) (Davis et al., 1989), Theory of Planned Behavior (TPB) (Ajzen, 1991), Technology Acceptance Model (TAM) (Davis et al., 1989) and Social Cognitive Theory (SCT) (Bandura, 1986). TAM was proposed by Davis in 1989. It was adopted from the TRA to predict and explain user acceptance and rejection of computer-based technology (Davis et al., 1989). It was attempted to provide a basis to study the effect of external variables on user behavior by identifying some basic variables as determinants of