Information technology in the past decade has drastically changed the human resources function. Providing support for mainly administrative activities such as payroll and attendance management in the beginning, information technology today enhances many of the recruitment function’s subprocesses such as longand short-term candidate attraction, the generation, pre-screening, and processing of applications or the contracting and onboarding of new hires. Online job advertisements on corporate Web sites and Internet job boards, online CV databases, different forms of electronic applications, applicant management systems, corporate skill databases, and IS supported workflows for the contracting phase are only few examples of the various ways by which information systems today support recruitment processes. However, little attention so far has been paid to the question of how these different forms of software support are effectively adopted by employers and how the interplay between HR departments, specialized departments, shared service centers and external service providers can be understood on an organizational level. Therefore, our research questions within this article are how do human resources information systems (HRIS) diffuse along the recruitment process? How can we explain the phenomena empirically observed? In order to answer these questions, we outline the literature on IS adoption and diffusion. Then, building on own longitudinal qualitative and quantitative research, we present a theoretically and empirically grounded framework of HRIS adoption and diffusion for the recruitment function.
The adoption and diffusion of information technology is among the most researched fields within the IS discipline. While this research in the beginning emerged from more general approaches to the adoption of innovation such as Rogers (1983) modeling individuals’ adoption of different forms of innovation, these models on the level of the individual later were complemented by research on the organizational process of IT adoption and diffusion. Today, hybrid models such as Gallivan (2001) can be found that combine individual and organizational adoption decisions and processes.
As the former models tried to identify those factors that account for an individuals’ adoption or non-adoption of a certain technology, models explaining these individual decisions are also referred to as factor models. Among the most important work in this field are Rogers’ (1983) diffusion of innovation (DOI) theory and the technology acceptance model (TAM) by Davis, Bagozzi, and Warshaw (1989). DOI theory, for example, identified the characteristics of the innovation, the social system and the communication channels used as factors influencing adoption decisions. These factors were considered to interact over time (Prescott & Conger, 1995). Several extensions to DOI theory recognized additional influential factors such as managerial support (Leonard-Barton & Deschamps, 1988), knowledge burdens (Attewell, 1992), and social contacts (Katz & Shapiro, 1986). Compared to DOI, Davis in this TAM framework shifted the focus from the external factors explaining individual adoption to the explanation of individuals’ internal beliefs, attitudes, and intentions. With perceived usefulness and perceived ease of use Davis identified two factors impacting individuals’ acceptance of IT (1989). While Fichman (1992) argued that these two factors were “essentially the same” as the relative advantage and complexity identified by DOI theory, other researchers such as Mathieson et al., (2001), Taylor and Todd (1995), and Venkatesh and Davis (2000) further extended TAM proving the explanative power of additional factors on technology acceptance.