Towards a Decomposed Expectation-Confirmation Model of IT Continuance: The Role of Usability

Abstract

Abstract:We propose a decomposed expectation confirmation model of IT continuance by 1) decomposing user expectation and confirmation into two dimensions of usefulness and usability, 2) conceptualizing the role of usability in IT continuance research, and 3) exploring changes in user perceptions of usability and usefulness over time and their impacts on user satisfaction and continuance intention. We tested the proposed research model using longitudinal data that we collected in two points in time six months apart from 125 users of the LinkedIn professional social networking site (pSNS). The results show that 1) perceived usability, usability confirmation, perceived usefulness, and usefulness confirmation determined user satisfaction with pSNS and 2) perceived usability along with satisfaction predicted continuance intention, whereas perceived usefulness had no effect. This study contributes IT continuance research by 1) proposing and empirically validating a decomposed model of IT continuance and 2) by bringing in usability as a core construct of interest for IT continuance research.

What drives subscribing to premium in freemium services? A consumer value‐based view of differences between upgrading to and staying with premium

“…Hence, this study advances the prior literature by providing a more nuanced understanding of the motivational and cognitive mechanisms affecting users' decision making regarding their post-adoption engagement with freemium services. Considering the pervasiveness of the freemium model across industries, this study extends the investigative locus of the prior IS literature on online service users' post-adoption behaviors (Kim & Son, 2009, Saeed & Abdinnour, 2013, Pan et al, 2017, Parthasarathy & Bhattacherjee, 1998, Li, Hongxiu & Liu et al, 2014 and online service continuance (Bhattacherjee, 2001a;Islam et al, 2017;Li et al, 2015;Mäntymäki, Merikivi, Verhagen, Feldberg, & Rajala, 2014;Zhou et al, 2012).…”

“…In IS literature, the most widely examined post-adoption behavior in online services is arguably continued service use, ie, continuance (Islam, Mäntymäki, & Bhattacherjee, 2017). Some studies investigated online service continuance in conjunction with other post-adoption behaviors such as word of mouth (Chea & Luo, 2008;Li, Liu, Xu, Heikkilä, & van der Heijden, 2015) and purchasing of value-added features (Mäntymäki & Salo, 2011).…”

Understanding the Effects of Temporal Differences in User-Centered Workflows on Solution Satisfaction

“…In effect, different contexts provide researchers opportunities to measure users' several unique expectations about a phenomenon. Recently, Islam and colleagues [16] proposed a decomposed expectation-confirmation model of IT continuance and posited role of perceived usability at different measurement times (i.e., t1 and t2). The study focused on a unique expectation variableperceived usability.…”

“…The literature on IS continuance employs variables, like perceived usability, usefulness and enjoyment to capture user system-related experiences [14,30]. Different types of systems, thus, provide different user experiences [16]. In this study, workflow agreement is proposed as a system experience construct to understand how the technology-induced workflow change impacts user affective processes in addition to task performance, which is assumed as essential for optimizing the usage extent and productivity [30].…”

“…In this study, workflow agreement is proposed as a system experience construct to understand how the technology-induced workflow change impacts user affective processes in addition to task performance, which is assumed as essential for optimizing the usage extent and productivity [30]. Furthermore, the study examines how system experience and task performance before and after workflow transition influence users' emotional development in terms of expectation and confirmation [5,16,21]. The eventual outcome variable is user satisfaction that has been recognized as the strongest predictor of continuous product engagement [5,15].…”