Post-adoption switching behavior for online service substitutes: A perspective of the push–pull–mooring framework
Highlights
► We explored factors that lead users to switch between online service substitutes. ► Based on pull–push–mooring framework, we develop a model with six hypotheses. ► Data are drawn from an online survey of 319 bloggers and analyzed by PLS technique. ► The push and pull effects both have positive influences on switching intention. ► The mooring effects have negative influence and moderating effect.
Introduction
The prevalence of the Internet means that information systems are used not only for commercial purposes but also as part of most people’s daily lives. Diversified online services satisfy these users’ various needs. Thus many studies consider online service adoption (e.g., Cheng, Lam, and Yeung (2006)), as well as post-adoption behaviors (e.g., Vatanasombut, Igbaria, Stylianou, and Rodgers (2008)). These latter behaviors are complex and can produce various outcomes. Most studies investigate the continuous usage of an online system, noting the importance of continuous usage for firm survival, especially in settings such as online banking or retailing (Bhattacherjee, 2001). In addition to continuous usage, post-adoption behaviors also might entail switching—an interesting topic that thus far has not been well investigated (Zhang, Lee, Cheung, & Chen, 2009).
From a relationship marketing perspective, maintaining long-term relationships with customers is an important managerial goal, mainly because of the high cost of acquiring new customers. It is also critical for online providers to retain a maximum number of users to keep expanding their profits and enjoy consistent advertising revenues (Zhang et al., 2009). The competitive environment that surrounds online services has prompted some researchers to focus more on user switching behaviors. For example, Kim, Shin, and Lee (2006) investigate factors that influence users’ switching intentions toward e-mail services, and Zhang et al. (2009) consider bloggers who switch among blog service providers. However, the continued rapid growth of Internet technologies and services suggests that online service providers constantly face new challenges from new technologies, as well as from the increasingly blurred business boundaries across companies. In particular, the level of substitution across online services may affect the competitive strategy of online service providers, which suggests the need for more precise explorations of this issue.
A growing field considers the development of blogs. When they emerged in the mid-1990s, blogs became a popular form of social networking that enabled users to present themselves and interact with others (Ip & Wagner, 2008). However, some practical findings indicate that many blogs have been abandoned, because bloggers lose interest or do not update their contributions regularly (Arnold, 2005, Hsu and Lin, 2008, Li and Walejko, 2008, Technorati, 2008). According to the Pew Internet & the American Life Project (PewInternet, 2010a, PewInternet, 2010b), blogging by young adults has decreased, and it appears that young users instead are moving more toward social networking sites (SNS), such as Facebook (Kopytoff, 2011, Quenqua, 2009, Silver, 2010). The prevalence of SNS suggests a potential substitution effect for blogs. Considering the importance of switching behavior across online services for online service providers, we examine the forces that drive increased switching from blogs to SNS.
To do so, we propose a push–pull–mooring (PPM) framework to delineate the determinants of substitution of online services, specifically between blogs and SNS. To begin, we summarize prior literature pertaining to post-adoption behaviors, consumer switching, and the PPM framework. In Section 3, we present our research model, then report the results of our empirical study. We conclude by discussing the implications of our findings, as well as some limitations and directions for further research.
Section snippets
Information system post-adoption behavior
Most literature on online service post-adoption behavior has focused on users’ continued use, after their initial acceptance or adoption of a specific information system, such as an online bank (Vatanasombut et al., 2008), Web-based learning (Chiu & Wang, 2008), or an electronic tax system (Hu, Brown, Thong, Chan, & Tam, 2009). In this sense, post-adoption usage is independent of initial adoption choices, because users’ experience with the system grants them new input that they can use to
Research model and hypotheses
Using the PPM framework as a general guideline, we develop a set of hypotheses to predict online service switching behaviors (Fig. 1). The push, pull, and mooring effects all are multidimensional constructs that aggregate several subconstructs (Law et al., 1998, Petter et al., 2007). These first-order subconstructs serve as formative indicators for the second-order constructs (i.e., the three effects in the PPM framework), though they are measured by reflective indicators. As dependent
Instrument
The measurement items come from extant literature and were modified slightly to fit the study context; we provide the full list of items in Appendix A. Because Facebook is the most popular SNS, we chose it as our research target (Lin and Lu, 2011, PewInternet, 2010b). The three items we used to measure a perceived weak connection came from Van Slyke et al. (2007); the three items used to assess writing anxiety were adapted from Daly and Miller (1975). For relative enjoyment, we adopted three
Tests for reliability, validity, and common method variance
We applied partial least squares (PLSs) using SmartPLS 2.0 (Ringle, Wende, & Will, 2005) to assess the psychometric properties of the scale and the structural model. This latent structural equation modeling technique uses a component-based approach and supports the integration of both measurement and structural models. Furthermore, PLS allows latent constructs to be modeled as formative or reflective indicators (Fu, 2011, Keil et al., 2000), which was necessary for our model.
To examine the
Discussion
With this study, we have explored several factors that might lead Internet users to switch among online service substitutes (i.e., blogs to SNS). Using the PPM model derived from human geography literature, we explain why young adult bloggers may be willing to transfer to other SNS (e.g., Facebook). The push effects, which consist of perceived weak connections and writing anxiety in relation to the blogs, exert positive influences on switching intentions. The pull effects, or the relative
Study limitations and further research
Several limitations should be considered when interpreting the results of this study; they also suggest possible directions for further research. First, our results cannot automatically be generalized to other samples and test situations. Our research target included primarily young adults, in accordance with the Pew Internet & American Life Project’s Report (PewInternet, 2010a), and the switching behaviors of older cohorts might differ. Further research thus should analyze any differences in
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