Research report Understanding information proactiveness and the content management system adoption in pre-implementation stage Yujong Hwang a, b, * , Mohanned Al-Arabiat c , Dong-Hee Shin d, ** , Younghwa Lee e a DePaul University, USA b Kyung Hee University, Republic of Korea c Princess Sumaya University for Technology, Jordan d Sungkyunkwan University, Republic of Korea e Miami University, USA article info Article history: Received 15 May 2015 Received in revised form 1 July 2016 Accepted 22 July 2016 Keywords: Information proactiveness Perceived ease of use Perceived usefulness Attitude Perceived behavioral control abstract The overall technology acceptance literature does not pay sufficient attention to the issue of the mandated use of systems as the traditional acceptance models (e.g. TAM) were originally built, tested, and validated by being applied to technologies that were mainly voluntary in nature, that is, the users had the choice of whether to use or not use the technology. Few have studied end users' proactive motivation to use information and attitude toward newly implemented technologies within organiza- tional contexts, before end-users start using the technology or pre-implementation stage. This research proposes that information proactiveness has influences on the content management systems adoption beliefs such as perceived ease of use and perceived usefulness. The proposed model was empirically tested using the data collected from content management systems end-users. As theorized, information proactiveness was found to be a significant determinant of system users' perceived ease of use but not perceived usefulness in pre-implementation stage. Furthermore, perceived behavioral control was found to be a strong determinant of systems users' attitude. The study findings provide important insights on enhancing system users' adoption behavior in pre-implementation stage. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction From an Information Systems (IS) perspective, acceptance and system use have been the variables of choice for measuring system success (DeLone & McLean, 1992; 2003; Goel, Hart, Junglas, & Ives, 2016; Ouirdi, Ouirdi, Segers, & Pais, 2016). However, within orga- nizations where most system usage is mandatory, intention-to-use or actual usage by and large don't present us with the benefit of seeing a clearer picture of how such use came to be or, more importantly, if such use is truly representative of how end users really feel about their use. As such, user satisfaction has been sug- gested as a “better” measure for success when usage is mandatory (DeLone & McLean, 1992). Interestingly but not surprisingly, the user satisfaction literature has failed to provide acceptable levels of explanatory and predictive power for system usage (Wixom & Todd, 2005). Attitude theories such the Theory of Reasoned Action (TRA) and its successor the Theory of Planned Behavior (TPB) are powerful in the sense that they provide researchers with the ability to both predict and explain behaviors (Ajzen, 1991; Fishbein & Ajzen, 1975; Jafarkarimi, Saadatdoost, Sim, & Hee, 2016). Their relative success in explaining and predicting behavior, such as system use, came as a result of their foundational premise that the attitudes people hold toward behaviors are better predictors of their behaviors than the attitudes they hold toward the object of the behavior. As new technologies, processes, procedures, and systems continue to infiltrate the world of organizations, research on potential adopters' acceptance of innovations is still receiving attention from pro- fessionals as well as academic researchers. Developers of new technologies, senior management, and those who are responsible for managing the changes associated with the implementation of innovations are increasingly realizing that the lack of user accep- tance can, and most probably will, lead to losses in resources, not to mention the possible effects on organizations' bottom line. * Corresponding author. DePaul University, USA. ** Corresponding author. E-mail addresses: yujongh@yahoo.com (Y. Hwang), dshin@skku.edu (D.-H. Shin). Contents lists available at ScienceDirect Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh http://dx.doi.org/10.1016/j.chb.2016.07.025 0747-5632/© 2016 Elsevier Ltd. All rights reserved. Computers in Human Behavior 64 (2016) 515e523