Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 2,223

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Gender Differences in the Perception and Use of E-Mail: An Extension to the Technology Acceptance Model1

Gefen, David, Straub, Detmar W.·1997·MIS Quarterly

Abstract

This study extends the TAM model (Davis 1989) and the SPIR addendum (Straub 1994) by adding gender to an IT diffusion model. The technology acceptance model (TAM) has been widely studied in IS research as an explanation of the use of information systems across IS types and nationalities. While this line of research has found significant cross-cultural differences, it has ignored the effects of gender, even though in socio-linguistic research, gender is a fundamental aspect of culture. Indeed, socio-linguistic research has shown that men tend to focus discourse on hierarchy and independence, while women focus on intimacy and solidarity. This literature provides a solid grounding for conceptual extensions to the IT diffusion research and the technology acceptance model. Testing gender differences that might relate to beliefs and use of computer-based media, this study sampled 392 female and male responses via a cross-sectional survey instrument. The sample drew from comparable groups of knowledge workers using e-mail systems in the airline industry in North America, Asia, and Europe. Study findings indicate that women and men differ in their perceptions but not use of e-mail. These findings suggest that researchers should include gender in IT diffusion models along with other cultural effects. Managers and co-workers, moreover, need to realize that the same mode of communication may be perceived differently by the sexes, suggesting that more favorable communications environments might be created, environments that take into account not only organizational contextual factors, but also the gender of users. The creation of these environments involves not only the actual deployment of communication media, but also organizational training on communications media.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2307/249720

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 2,223

Metadata

Authors
Gefen, D., & Straub, D. W.
Venue
MIS Quarterly
Publisher
MIS Quarterly
Published
1997-12-01
Volume
21
Issue
4
Pages
389-400
ISSN
  • 0276-7783 (ISSN-L)
  • 2162-9730
OpenAlex
W1584405424
Cited by
2,223
References
4
FWCI
66.42
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.