Data · dataset · 2011
Similarities and Differences of Factors Influencing Motorist\'s Acceptance Before and After the Implementation of Freeway\'s Electronic Toll Collection System: A View from Information Dissemination Channels
Listed in Harvard Dataverse
Word-of-mouth, as refer to the passing of information from person to person, is an important marketing strategy for product promotion.
Description
Besides, information disseminated through media is so common in nowadays’ life and, thus, their comments of a commodity or service, as well as the information exchanged by face to face interaction, might affect people’s final choice eventually. In this study we focus on how the contents disseminated through different word-of-mouth channels(face to face communication and electronic media which includes the conventional media and the Internet) about the electronic toll collection(ETC) system, a new toll collection service in Taiwan, affect the acceptance intention of highway drivers on it.
Through the collected survey data about the evaluations of highway drivers before and after this system been implemented from different channels, we investigate how the evaluation changes influence their acceptance intention of the ETC system. After the estimation of structural equation models, we find that the evaluation changes by word-of-mouth from electronic media and face to face directly, and the “perceived easy to use” and “social norm” indirectly, affect the acceptance intention of ETC system on highway drivers in Taiwan.
Links
Where it is published
- Dataverse dataset page dataverse.harvard.edu/dataset.xhtml?persistentId=doi%3A10.6141%2FTW-SRDA-E98027-1 ↗
landing page · from Harvard Dataverse
- DOI doi.org/10.6141/tw-srda-e98027-1 ↗
DOI / persistent id · from Harvard Dataverse
Catalogue records · 1
- Dataverse API dataverse.harvard.edu/api/datasets/:persistentId/?persistentId=doi%3A10.6141%2FTW-SR… ↗
metadata API · from Harvard Dataverse
Provenance · 1 source records, 5 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Harvard Dataverse | doi:10.6141/TW-SRDA-E98027-1 | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| created_date | source · Harvard Dataverse | connector:dataverse@1.0.0 | |
| description | source · Harvard Dataverse | connector:dataverse@1.0.0 | /description |
| publication_date | source · Harvard Dataverse | connector:dataverse@1.0.0 | |
| title | source · Harvard Dataverse | connector:dataverse@1.0.0 | /name |
| updated_date | source · Harvard Dataverse | connector:dataverse@1.0.0 |