Continued user engagement and motivational information systems

Engagement. The objective of MIS is to guide users towards appropriate behaviors to achieve their system-related goals in domains such as education, fitness, or nutrition, where continued performance of goal-related activities is key to success. To establish such behaviors, users need to frequently engage with the systems (Servick, 2015). Engagement—understood as the user’s motivationally driven, volitional investment of resources into interactions with a system (Brodie et al., 2011; Hollebeek et al., 2019)—encompasses cognitive, emotional, social, and conative dimensions. Because these different dimensions will ultimately manifest in actual engagement behavior (Brodie et al., 2011; Hennig-Thurau et al., 2010), we focus on the latter to conceptualize continued user engagement which refers to the time and effort invested by the user in the service system (Flaherty et al., 2019).

In the context of information systems, prior research has focused on frequency of use to examine continued user engagement (e.g., Rutz et al., 2019). We argue that the intensity of use represents an additional constituting facet of continued user engagement in the context of MIS since it indicates the effort made in performing goal-related activities as well as the investment in the relationship with the service (provider) and hence the qualitative component of engagement.

Thus, in the present research, we distinguish between engagement frequency as the number of system use episodes in a given time period (i.e., “quantity” of encounters), and engagement intensity as the length of a system use episode indicating a user’s stickiness (i.e., “quality” of encounters; Dagger et al., 2009; Deci & Ryan, 2000; Gupta et al., 2004).

Motivational information systems. User engagement depends on the expected value drawn from experiences arising during system use (Brodie et al., 2011; Vivek et al., 2012). To engage users continuously, systems are designed to facilitate a wide array of experiences that provide value

to the user (Stocchi et al., 2018). In the context of media engagement, Calder et al. (2009) and Stocchi et al. (2018) argue that the experiences should provide utilitarian as well as hedonic value.

MIS are specifically designed to offer both (Koivisto & Hamari, 2019). By supporting users in achieving their goals, MIS provide utilitarian value (i.e., reaching a goal that is separate from the system use itself; Davis, 1989). At the same time, the users should enjoy interacting with the systems, offering hedonic value (i.e., having fun when using the system; van der Heijden &

Heijden, 2004). More precisely, the objectives of MIS’ use are related to effectiveness and thus utilitarian, however, the means by which the systems promote effectiveness are hedonic in nature (Koivisto & Hamari, 2019). To provide hedonic value to users and to enhance continued engagement, MIS draw on design principles of hedonic services. The most established MIS designs are based on games and social networks (Hassan et al., 2019; Koivisto & Hamari, 2019). Games are played for their own sake, as people enjoy them (Ryan et al., 2006). By implementing features of games such as points, badges, or leaderboards in information systems, providers aim to arrange goals in a SMART (i.e., specific, measurable, achievable, relevant, and time-bound) way and supply users with informational and affective feedback (Hamari et al., 2018; Huotari & Hamari, 2017; Wolf et al., 2018). Social networks leverage the nature of human beings by providing a sense of belonging and help to define oneself through social feedback (Festinger, 1954; Liu et al., 2013;

Ryan & Deci, 2002). Service providers aim to afford social support by embedding features of social networks such as friending, sharing, or social feedback (e.g., thumbs up). While some features cannot exclusively be allocated to one of the design principles (e.g., groups or leaderboards), most MIS often combine features of different principles. Nowadays, MIS are well established in various domains such as fitness (Freeletics, Nike+), education (Duolingo, Babbel), and habit formation (Habitica, stickK).

Previous literature on MIS and engagement. Several qualitative studies in the domains of brand communities, healthcare, and co-creation indicate that MIS could lead to enhanced behavioral engagement (Hammedi et al., 2017; Harwood & Garry, 2015; Leclercq et al., 2017;

Robson et al., 2016). These results are in line with quantitative studies showing that MIS positively affect behavioral engagement intention (Eisingerich et al., 2019; Leclercq et al., 2018, 2020). In the domains of health and dating, Eisingerich et al. (2019) found that design principles of MIS enhance system use intention. In several experiments, Leclercq et al. (2018, 2020) demonstrated that depending on the design, MIS can enhance the intention of participation in co-creation communities. Further, previous studies have shown that MIS can enhance the willingness to pay for a service and increase the intention of referrals (Stocchi et al., 2018; Wolf, Weiger, et al., 2020), which are both considered as outcomes of behavioral engagement (Kumar & Pansari, 2016).

Additionally, Zimmerling et al. (2019) have experimentally found that MIS design can enhance the quantitative output in an idea contest, but not the quality.

In summary, these findings indicate that MIS can increase actual engagement behavior even if this has not yet been confirmed empirically. However, these studies do not address whether MIS can actually promote continued user engagement, or whether it fades after the initial attraction, as studies only capture the intention to engage which users often fail to enact (Etkin, 2016; Liu et al., 2017; Wemyss et al., 2019). In addition, while previous research focused on the effects of MIS on the intention to engage frequently, the influence on engagement intensity as an indicator of the quality of the behavior has so far been neglected. This is surprising because engagement intensity is crucial to the success of many business models of digital service providers as well as to the achievement of users’ goals (Appel et al., 2020; Devezer et al., 2013).

Previous literature on how MIS drive engagement. As stated previously, to achieve continued user engagement, MIS are designed to let the user draw hedonic value from using the system itself,

beyond the utilitarian benefit of supporting the users’ goal achievement. In order to do so, such systems focus on making the usage more enjoyable and perceived as self-regulated (Koivisto &

Hamari, 2019; Liu et al., 2017). Even though the psychological processes of MIS have been examined by prior studies, it is still unclear which mechanisms MIS actually trigger to drive behavior (Koivisto & Hamari, 2019). In fact, prior research indicates that MIS may drive behavior in different ways (Landers et al., 2019; Mekler et al., 2017; Sailer et al., 2017; Xi & Hamari, 2019).

While some studies show that MIS foster need satisfaction (e.g., Sailer et al., 2017; Xi & Hamari, 2019), others find no effect (e.g., Landers et al., 2019; Mekler et al., 2017) and suggest that MIS only foster extrinsic motivation. However, the consideration of different but simultaneously triggered psychological paths to explain these inconclusive findings has been neglected so far. To close this gap, we will next draw on SDT to explain the different psychological processes that may occur during MIS use.