The impact of national culture traits on the usage of web 2.0 technologies
Bibliographic record
Abstract
Purpose Web 2.0 technologies are becoming popular and are being used not only for social networking but also to facilitate communication and increase knowledge sharing in the work environment. Extensive research has been conducted in the past to understand the factors affecting the adoption and use of IT systems but few have studied the influence of national culture on such adoption models. When it comes to web 2.0 usage, the literature is only emerging and the role of national culture has not been addressed. The purpose of this paper is to fill this gap. Design/methodology/approach In order to better understand the factors that affect the use of web 2.0 technologies and the influence of national culture on it, data were collected from 376 young adults in the age range of 18‐29 from the USA, Thailand and Bahrain. A model was developed and statistically tested to understand the influence of national culture traits, social grooming aspects, efficiency, online privacy, perceived usefulness, subjective norms and gender. Findings Based on the type of web 2.0 usage (expressive or instrumental) different variables were demonstrated to be significant predictors. For expressive usage, uncertainty avoidance, maintaining relationships, online privacy and perceived usefulness were significant. For instrumental usage, long‐term orientation and perceived usefulness were significant. A ranking of various types of web 2.0 usage was also created, showing very few differences among countries. Research limitations/implications This research is the first step in a series of research activities that should be conducted to better understand the influence of culture in the adoption and usage of web 2.0 technologies. The sample was composed only of “Millennial” generation students and should be extended to other generations and to other countries with markedly different cultural profiles. Practical implications The findings of the paper help to better understand the usage of web 2.0 technologies by young adults who are about to enter the labor market and are likely to use Enterprise 2.0 applications in their work environment. Since web 2.0 technologies are centered on the concepts of communication, collaboration and information sharing, they will influence the behavior of future knowledge workers in terms of knowledge sharing. Accordingly, better understanding of web 2.0 use will help to improve the understanding of Enterprise 2.0 and knowledge management tools usage in a global environment. Originality/value This paper's original contribution stems from the fact that the influence of national culture on the use of web 2.0 has not yet been addressed in the literature.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".