Predicting Collaboration Technology Use: Integrating Technology Adoption and Collaboration Research

the paper presents a model integrating theories from collaboration research (i.e., social presence theory, channel expansion theory, and the task closure model) with a recent theory from technology adoption research (i.e., unified theory of acceptance and use of technology, abbreviated to utaut) to explain the adoption and use of collaboration technology. we theorize that collaboration technology characteristics, individual and group characteristics, task characteristics, and situational characteristics are predictors of performance expectancy, effort expectancy, social influence, and facilitating conditions in utaut. we further theorize that the utaut constructs, in concert with gender, age, and experience, predict intention to use a collaboration technology, which in turn predicts use. we conducted two field studies in Finland among (1) 349 short message service (SMS) users and (2) 447 employees who were potential users of a new collaboration technology in an organization. Our model was supported in both studies. the current work contributes to research by developing and testing a technology-specific model of adoption in the collaboration context. key worDS anD phraSeS: channel expansion theory, collaboration technologies, social presence theory, task closure model, technology acceptance, technology adoption, unified theory of acceptance and use of technology. technology aDoption iS one of the moSt mature StreamS in information systems (IS) research (see [65, 76, 77]). the benefit of such maturity is the availability of frameworks and models that can be applied to the study of interesting problems. while practical contributions are certain to accrue from such investigations, a key challenge for researchers is to ensure that studies yield meaningful scientific contributions. there have been several models explaining technology adoption and use, particularly since the late 1980s [76]. In addition to noting the maturity of this stream of research, Venkatesh et al. identified several important directions for future research and suggested that “one of the most important directions for future research is to tie this mature stream [technology adoption] of research into other established streams of work” [76, p. 470] (see also [70]). In research on technology adoption, the technology acceptance model (taM)  is the most widely employed theoretical model [76]. taM has been applied to a range of technologies and has been very predictive of individual technology adoption and use. the unified theory of acceptance and use of technology (utaut) [76] integrated eight distinct models of technology adoption and use, including taM. utaut extends taM by incorporating social influence and facilitating conditions. utaut is based in PrEDICtING COllaBOratION tEChNOlOGY uSE 11 the rich tradition of taM and provides a foundation for future research in technology adoption. utaut also incorporates four different moderators of key relationships. although utaut is more integrative, like taM, it still suffers from the limitation of being predictive but not particularly useful in providing explanations that can be used to design interventions that foster adoption (e.g., [72, 73]). there has been some research on general antecedents of perceived usefulness and perceived ease of use that are technology independent (e.g., [69, 73]). But far less attention has been paid to technology-specific antecedents that may provide significantly stronger guidance for the successful design and implementation of specific types of systems. Developing theory that is more focused and context specific—here, technology specific—is considered an important frontier for advances in IS research [53, 70]. Building on utaut to develop a model that will be more helpful will require a better understanding of how the utaut factors play out with different technologies [7, 76]. as a first step, it is important to extend utaut to a specific class of technologies [70, 76]. a model focused on a specific class of technology will be more explanatory compared to a general model that attempts to address many classes of technologies [70]. Such a focused model will also provide designers and managers with levers to augment adoption and use. One example is collaboration technology [20], a technology designed to assist two or more people to work together at the same place and time or at different places or different times [25, 26]. technologies that facilitate collaboration via electronic means have become an important component of day-to-day life (both in and out of the workplace). thus, it is not surprising that collaboration technologies have received considerable research attention over the past decades [24, 26, 77]. Several studies have examined the adoption of collaboration technologies, such as voice mail, e-mail, and group support systems (e.g., [3, 4, 44, 56, 63]). these studies focused on organizational factors leading to adoption (e.g., size, centralization) or on testing the boundary conditions of taM (e.g., could taM be applied to collaboration technologies). Given that adoption of collaboration technologies is not progressing as fast or as broadly as expected [20, 54], it seems a different approach is needed. It is possible that these two streams could inform each other to develop a more complete understanding of collaboration technology use, one in which we can begin to understand how collaboration factors influence adoption and use. a model that integrates knowledge from technology adoption and collaboration technology research is lacking, a void that this paper seeks to address. In doing so, we answer the call for research by Venkatesh et al.  to integrate the technology adoption stream with another dominant research stream, which in turn will move us toward a more cumulative and expansive nomological network (see [41, 70]). we also build on the work of wixom and todd [80] by examining the important role of technology characteristics leading to use. the current study will help us take a step toward alleviating one of the criticisms of IS research discussed by Benbasat and Zmud, especially in the context of technology adoption research: “we should neither focus our research on variables outside the nomological net nor exclusively on intermediate-level variables, such as ease of use, usefulness or behavioral intentions, without clarifying 12 BrOwN, DENNIS, aND VENkatESh the IS nuances involved” [6, p. 193]. Specifically, our work accomplishes the goal of “developing conceptualizations and theories of It [information technology] artifacts; and incorporating such conceptualizations and theories of It artifacts” [53, p. 130] by extending utaut to incorporate the specific artifact of collaboration technology and its related characteristics. In addition to the scientific value, such a model will provide greater value to practitioners who are attempting to foster successful use of a specific technology. Given this background, the primary objective of this paper is to develop and test a model to understand collaboration technology adoption that integrates utaut with key constructs from theories about collaboration technologies. we identify specific antecedents to utaut constructs by drawing from social presence theory [64], channel expansion theory [11] (a descendant of media richness theory [16]), and the task closure model [66], as well as a broad range of prior collaboration technology research. we test our model in two different studies conducted in Finland: the use of short message service (SMS) among working professionals and the use of a collaboration technology in an organization.