Understanding use continuance of social networking sites in organizations from employees’ perspectives: multicontextual contrasts between Canada and Cote d’Ivoire
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Limited research has espoused a comparative perspective to study social networking sites’ (SNS) use continuance despite most of them being abandoned after initial adoption. Most existing empirical works have been undertaken in western contexts, and they do not consider country-origin influence. Thus, they are of little benefit to global and transnational organizations. Awareness of countries’ similarities and contrasts provides the basis for understanding people’s behaviors in cross-cultural contexts, which can be crucial to ensuring technology acceptance and success, especially in multinational organizations. Our research aims to explain why and how people use SNSs sustainably in the workplace through a model and comparative study. Design/methodology/approach The theoretical framework was developed to integrate and extend two major behavioral adoption and technology use models in explaining SNS use continuance. This paper collected data through a survey and analyzed it using structural equation modeling through partial least squares (PLS). Findings One major contribution of this study is to highlight that the users in selected countries are driven strongly by subconscious factors rather than traditional factors based on the system attributes and users’ perceived rationality of continuing to use SNSs. Research limitations/implications This paper recommends that the model in this study be tested in other technology environments to evaluate the external validity of the research study. The research was based on an unspecified platform, but each SNS may have its own singularities that should merit further consideration. Originality/value This paper will contribute to the literature by integrating and extending two major theoretical frameworks and espousing a cross-national perspective.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it