Exploring Drivers of Platform Activity from Web and Mobile Users: A Quantitative Analysis

Public sector organizations increasingly make use of information and communication technologies to communicate with externals, among other things, for the benefit of public service quality and efficacy of service delivery... [ view full abstract ]

Public sector organizations increasingly make use of information and communication technologies to communicate with externals, among other things, for the benefit of public service quality and efficacy of service delivery (e.g., Lukensmeyer and Torres, 2008; Heipke, 2010; Royo and Yetano, 2015). They encourage citizens to participate in new platform-based forms of collaborative activities and to transfer their knowledge and experience to the organization (Linders, 2012; Nam, 2012; Mergel, 2015). Knowledge about the motivation of individuals who participate in this new service mode contributes to improve platform effectiveness and increase participation (Leimeister et al., 2009; Mergel and Desouza, 2013). Nevertheless, this innovative pattern of communication between administration and citizens through leveraging modern technology has hardly been systematically investigated by researchers. This contribution intends to close this research gap.

The objective of this current research is twofold. First, we attempt to identify the determinants of citizens’ participation in an open government. Then, as the second objective, we investigate the influence of the type of technological device as the reason for a difference in citizen attitudes and platform activity. In this regard, an empirical study was conducted (a) among citizens communicating with administration via web and (b) those using mobile devices for interacting. We ask the following questions: (1) What motivates citizens to engage in platform-based and government-initiated forms of collaborative activities? (2) What drives participants to actively contribute to administrative work? (3) Does platform behavior differ between citizens utilizing mobile devices and those participating via the web platform?

For answering these questions, we develop and test a model to explain citizens’ usage of web and mobile devices to interact with local government. We put forth an integrated model that explains citizens’ online participation in city improvement through extending the technology acceptance model (TAM) by motivation theory: (1) According to TAM (Davis, 1989), IT usage is determined by an individual’s behavioral approach to technology use, which is further influenced by an individual’s attitude towards using a system and its perceived usefulness. Technology acceptance is defined to be a function of perceived ease of use (PEOU) and perceived usefulness (PU) (Davis, 1989; Davis et al., 1989). These relationships have been empirically tested, among others (e.g., communication systems, specialized business systems, see Lee et al., 2003), in the public sector context (e.g., Carter and Bélanger, 2005; Suki and Ramayah, 2010; Kollmann et al., 2012). Based on the results of prior studies on citizens’ acceptance of technology provided by the government (e.g., e-government, e-democracy applications), first, we assume that perceived usefulness as the extent to which individuals perceive personal benefit from leveraging the platform is positively related to platform activity (Hypothesis 1). Although prior results on the effect of PEOU on technology acceptance are mixed, we add the variable to our framework due to the significance of PEOU in a non-workplace and voluntary usage context (Venkatesh et al., 2003; Venkatesh and Bala, 2008). Second, we thus hypothesize that perceived ease of use as the degree of ease expected from using the platform positively relates to platform activity (Hypothesis 2).

(2) Individuals’ platform activity depends on their willingness to interact with local government and collaborate for the benefit of city improvement. Based on research on motivation (e.g., Batson, 1998; Deci and Ryan, 2000), we assume that individuals’ motivation for engagement in government-initiated collaborative processes can be (a) intrinsic and (b) prosocial. First, intrinsic motivation, as “the doing of an activity for its inherent satisfaction rather than for some separate consequences” (Deci and Ryan, 2000, 260), refers to having fun and feeling enjoyment when performing an activity in contrast to having extrinsic motivation (see perceived usefulness). Based on empirical studies on motivation to participate in open-source projects (e.g., Lakhani and Wolf, 2005; Luthinger and Jungwirth, 2007; Osterloh and Rota, 2007) and citizens’ willingness to participate in collaborative projects (e.g., Wijnhoven et al., 2015), we hypothesize that users who feel fun and enjoyment when using the platform participate more actively (Hypothesis 3). Second, prosocial motivation, as the desire to expend effort to benefit other people (Batson, 1998), explains participation in open-source (e.g., Hars and Ou, 2001; Bryant et al., 2005; Lakhani and Wolf, 2005; Osterloh and Rota, 2007; Oreg and Nov, 2008) and voluntary engagement in online communities (e..g., Zeitlyn, 2003; Brabham, 2010; Kube et al., 2015). We thus assume that participants with high levels of prosocial motivation are more active on the platform (Hypothesis 4).

(3) Advances in ICT lead to increased provision of different kinds of online platforms where citizens can vote, participate in idea creation, interact with government, or exchange political viewpoints. Previous studies on participation in governmental activities showed that individual engagement in these activities via traditional channels correlates with their online participation behavior. A positive association between citizens’ activism via traditional channels or previous behavior and online engagement was confirmed in terms of e-government use (Dimitrova and Chen, 2006) or online consultation (Coleman et al., 2012). These results lend support for the influence of traditional and offline participation behavior on individuals’ engagement in online activities. We assume a similar effect in terms of service monitoring and suppose that citizens’ service-monitoring behavior via traditional channels prior to platform implementation positively influences platform activity (Hypothesis 5a). Furthermore, triggers for online political activity distinguish from those for offline activity (Nam, 2012). The influence of socio-demographics, civic attitudes, and attitude towards politics differ between online and offline political activity. Therefore, we anticipate a difference in predictors for monitoring activity for people who have engaged in service reporting previously, and “new” reporters, and that the strength of the relationship between predictors and participation behavior is affected by previous monitoring behavior (Hypothesis 5b).

For testing the research model, a survey was conducted among registered user of an online participation platform (N=773). The platform can be accessed via website and mobile phone. Quantitative research methods (i.e., principal component analysis, hierarchical linear regression analysis) are applied to test the hypotheses. Each hypothesis is tested for web and mobile users.