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In this research, we evaluated user participation and involvement in the context of enterprise resource planning (ERP) systems. Since ERP systems are enterprisewide in scope, these systems have a high level of complexity, and require a different implementation methodology. While most studies analyze implementation at an organization or industry level, there is a dearth in research in ERP system adoption at the individual or user level. In our study, we examine ERP system acceptance at the individual level. In this research, we expected to find differences in the nature of user participation and involvement in ERP compared to other information systems. Using Barki and Hartwick's extension of the theory of reasoned action, a revised model was developed and tested empirically. While Barki and Hartwick's model explains user behavior vis-à-vis user participation and involvement, a more parsimonious model demonstrates that usage dynamics in ERP implementation are different. We complemented our statistical analysis by three case studies. Based on our results we believe that, given the nature of ERP and its implementation, traditionally formalized links between influencers of users' attitude and involvement may need to be revised. We have discussed why we need to seek alternate forms of influencers. In doing so, we suggest that investments be made in preparatory work practices and employee development prior to ERP decisions. Such investments are complementary to information technology and are widespread throughout the firm. We believe that such investments will play a significant role in influencing the attitude of users toward any system and also their involvement.

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Impact of information technology on firm productivity has received significant attention in information systems literature. Although many studies were performed to investigate this effect, the results were not conclusive in supporting a systematic effect. This study investigates this phenomenon in both manufacturing and service industries by considering a sample of 85 manufacturing and 77 service firms. Our research methodology utilizes a combination of various data envelopment analysis models and non-parametric statistical techniques in testing for the influence of information technology investment on firm productivity. We investigate this effect under conditions of both constant and non-constant returns to scale assumptions. Our results provide some very interesting insights and recommendations.

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