IMPLICATIONS FOR INFORMATION SYSTEM THEORY

The work makes two main theoretical contributions which are not artifact specific.

2.1. An Imperative for Information Systems Success Research

The first theoretical contribution lies in studying the role of information systems success as post-acceptance variables in continued information systems use. Especially on an organizational level of analysis, there is a lack of empirical findings concerning the relationship between success variables and continuance intention (Petter et al. 2008; Urbach et al. 2009). Net benefits and system quality both explained a decent amount of the variance in continuance intention, showing the importance of post-acceptance success evaluations on the intention to continue the subscription of cloud-based ES. Interestingly, within Chapters 4 and 6², there was no significant correlation between information quality and continuance intention, even though information needs of the distinct stakeholder groups are among the most important IT executive concerns. Triggered by this finding, we conducted an exploratory stakeholder analysis in Chapter 5, revealing that information quality contributes to the prediction of continuance intention in the management cohort, but not in the strategic cohort.

The results propose that the prediction of continuance intention might be dependent on patterns and mechanisms which have yet to be identified and which cannot be reduced to an individual behavioral mechanism.

The information systems success model (DeLone and McLean 1992) and its revision (Delone and McLean 2003) have been criticized in various publications (e.g. Seddon 1997) for its questionable hypotheses network, which was developed based on the theory of communication (Shannon and Weaver 1949) using a content-based literature review. The information systems success model has often led to confusion as it is generally designed to be applied both, on an organizational level of analysis and an individual level of analysis (Petter et al. 2008). However, the success variables cannot all be applied on an organizational context. For instance, user satisfaction is an individual level variable solely, whereas system quality can both, be interpreted as organizational level and individual level variable. In this thesis only the success variables were included, but not the hypotheses suggested by the model. The success variables showed to adequately represent success, and showed to be a good predictor of organizational level continuance. This clarifies two things, which have to be

2 Note that the sample used in Chapter 4 is a subset of the sample used in Chapter 6. Hence, it is not surprising that the data analysis yields similar results, even though the measurement of the success dimensions differed between the Chapters 4 and 6.

addressed in future research on information systems success. First, the variables, which are applicable (e.g. information quality, system quality, and net benefits) are adequate and meaningful on an organizational level. Therefore, the variables themselves are a good representation of success by themselves and should be included in future research. This is especially supported by the fact that the information systems success variables captured all identified SaaS success dimensions exhaustively. Second, the mix of individual level and organizational level elements concerning the whole information systems success model leads to misinterpretation and false accumulation of empirical knowledge. Research in this area will have to clearly separate organizational level information systems success and individual level information systems success, leading to distinct theoretical perspectives, models, and hypotheses development, which makes it necessary to completely revise the existing body theoretical contributions on information systems success (especially on an organizational level). This also relates to the criticism of Prof. Dr. Peter Mertens (Buhl et al. 2010), who validly points out that professional information systems are installed to support an organization, hence, its success should be assessed related to its organizational impact and organizational effectiveness.

2.2. The Divergence of Adoption, Continuance, and Discontinuance Research

The second theoretical contribution of the thesis, especially regarding Chapter 6, is the provision of an organizational level continuance framework. In this effort, it was possible to integrate elements of the discontinuance framework (Furneaux and Wade 2011), which showed to be important variables in explaining the variance of the dependent variable. In this case, it was shown that variables, which influence discontinuance intention in latter stages of the information systems lifecycle, are also meaningful even in an early stage after adopting the system.

It is clear that the importance of variables varies between the different stages of the information systems lifecycle or adoption scenarios. For instance, it makes a difference if a system is adopted and the system to be replaced is highly embedded within an IT infrastructure or an information system is newly added on top of an existing infrastructure. In the first case, the organization might decide not to replace the system due to unpredictability of system failures (e.g. Furneaux and Wade 2011), whereas in the second case this disposition does not play a role. Hence, clearly differing between these stages is an imperative for information systems research (especially when considering cross-sectional research design), which is not considered even in the case of recent top publications (Jeyaraj et al. 2006), where

adoption and continuance are not clearly defined (e.g. continuance starts after the system has been implemented, which has to be noted in the survey). This is especially true for organizational level research, where only few papers exist studying continuance and discontinuance of information systems (Furneaux and Wade 2011). Given the findings of this thesis, where we found variables of discontinuance research being relevant in an early stage of continuance, future research on organizational level adoption, continuance, and discontinuance will have to clearly distinguish the three stages, and in a next step, find interferences between the variables in distinct stages. For instance, as the results of the thesis suggest, technical integration is a variable which is both relevant in an early and late stage of the information systems lifecycle.

3.