Data · dataset · 2007
Impact of Leadership Competencies and Employee Job Satisfaction on Productivity in Design Industry
Listed in Harvard Dataverse
In this modern society, it is a common desire to search for innovative and different designing ideas.
Description
For design industries, organizational management is an important issue for product development and design. Problems such as ill-supervision, unclear definition of goals, distorted direction in designing analysis, and defects in concept formation are all regarded as the consequences of improper organizational management (Deng Chen-Lien, 1999).
Outstanding product design relies on excellent leadership and management. However, employees are the most precious asset in the organization. Their motivation and self-perception would influence performance and behavior.
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Employee’s job-satisfaction is an important factor determining productivity. There are many factors that would influence employees’ perception on job-satisfaction. Recent researches indicated that supervisor’s leadership has an obvious impact on employees’ job-satisfaction.
However, there have been only a few studies on how leadership brings about job-satisfaction and productivity, especially in the design industries. It is a critical process for leaders to understand how leadership would influence subordinates’ perception on job-satisfaction (Fang Jiun-Ru, 1990). This research explored the inter-relationship among supervisors’ leadership competences, employee job-satisfaction and productivity in design industries.
There are three major instruments in the research: (1) Leadership Competence Assessment Instrument (LCAI), a localized instrument developed by Chen Yi-Chun and Yeh Lien-Chi (1996); (2) Minnesota Satisfation Questioniare (MSQ), based on the development by Weiss et al. (1967); (3) Employee productivity instrument (EPI), developed by Lee Yuan-Duen and Lain Jing-Wei (2000). The sampling subjects in this research were the employees in the designing industries.
We divided them into four categories as: product design, fashion design, commercial design, and interior design. Portion sample in the Stratified Random Sampling techniques was used. We balanced the portion of gender, age, years of experience, and position in the sample to reduce sampling errors because of over-concentration in one specific portion. 400 questionnaires were distributed, 100 for each category. 256 questionnaires were returned with a return rate of 66.25%.
The result of this research not only can be compared for other relevant researches, but also a good reference for the managing of the designing industry.
Links
Where it is published
- Dataverse dataset page dataverse.harvard.edu/dataset.xhtml?persistentId=doi%3A10.6141%2FTW-SRDA-E91048-1 ↗
landing page · from Harvard Dataverse
- DOI doi.org/10.6141/tw-srda-e91048-1 ↗
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
Topics
- Inferred from text
- Human resources and industrial relations 73%
Provenance · 1 source records, 6 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Harvard Dataverse | doi:10.6141/TW-SRDA-E91048-1 | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3505 | enrichment · Harvard Dataverse | taxonomy-embedding@1.1.0 | title+keywords+description (73%) |
| 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 |