IMPACT OF SUPER USER SUPPORT ON USER PERCEPTIONS AND SATISFACTION WITH INTEGRATIVE TECHNOLOGIES: A SOCIAL PRESENCE PERSPECTIVE
Bibliographic record
Abstract
Enterprise Information Systems (EIS) are large systems that enable the integration of business processes and allow seamless business process data flow throughout the organization. An EIS implementation is considered a failure if it is being cancelled; if it is removed early with relevant financial and organizational losses; or if the implementation resulted in a system being underutilized due to dissatisfaction, overspend or poor requirements gathering. Despite excessive spending over the years on digital transformation projects of such systems, failure rates have been excessively high. This research explores Super User effectiveness as an integral part of digital transformation processes. Super Users are regular but highly motivated employees who receive additional training in the use of a new or upgraded computer system to be introduced in the workplace, so that they can provide first-line technical support and training to their local colleagues. Super Users are frequently engaged in guiding and supporting users throughout and after EIS implementations or system upgrades. User satisfaction with the training process and Super User support effectiveness tends to contribute to more successful system transition and EIS implementation success. However, the role of Super Users in EIS implementations as a first line of education and support for EIS users has been substantially understudied as a potential way of reducing these failure rates. Although several studies have explored desired Super User characteristics in EIS systems implementation and successful organizational digital transformation processes, there has been a lack of attention to user perceptions of integrative systems as a contributing factor to better system utilization and implementation. This research explores Super User effectiveness as an integral part of digital transformation processes. A Theoretical Model was developed that draws from accepted theories of collaborative technology, technology adoption, and expectation confirmation. A survey was used to gather responses of 321 end users about their perceptions of Super User support and effectiveness, derived from their experience in several organizations that had undergone digital transformation. The study data were analyzed quantitatively, and the model validated through a structured equation model that was developed, based on relevant published models. A further explanatory study was conducted through thematic analysis of written participant responses. Our study found that Super User ability to emphasize the collaborative features of integrative systems by augmenting user perceptions of EIS as a social presence medium can contribute to higher levels of user performance and satisfaction. Immediacy of integrative systems as well as Individual user characteristics were found to play a positive role in user performance and satisfaction improvement. Situational characteristics of resource-facilitating conditions was also found to contribute positively to user performance and satisfaction. This study contributes to existing research on integrative systems characteristics and Super User effectiveness. It emphasizes collaborative components of integrative systems and discusses additional tools and expanded capabilities for systems utilization and user learning. It also expands on our understanding of Super User effectiveness through an exploration of user perceptions of integrative systems as a social presence medium and effective collaboration tool. Practitioners can thereby emphasize to users the resulting augmented capabilities that can contribute to effectiveness of the Super User training and development process. Practitioners should therefore urge organizations to focus on Super User selection and development as effective organizational resources that facilitate user support through organizational changes associated with EIS implementations, thereby contributing to increases in EIS implementation success rates.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".