Evidence map›Paper›PMID 27139697›Full record

ArticlePloS one2016

Using a Mixed Model to Evaluate Job Satisfaction in High-Tech Industries.

Sang-Bing Tsai, Chih-Yao Huang, Cheng-Kuang Wang, Quan Chen, Jingzhou Pan, Ge Wang, Jingan Wang, Ta-Chia Chin, Li-Chung Chang

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. An Empirical Study on Low-Carbon: Human Resources Performance Evaluation.International journal of environmental research and public health · 2018
    Article
  3. The Development Evaluation of Economic Zones in China.International journal of environmental research and public health · 2018
    Article
  4. Article
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sang-Bing TsaiZhongshan Institute, University of Electronic Science and Technology of China, Guangdong, 528402, China.
Chih-Yao HuangBusiness School, Nankai University, Tianjin, 300071, China.
Cheng-Kuang WangZhongshan Institute, University of Electronic Science and Technology of China, Guangdong, 528402, China.
Quan ChenZhongshan Institute, University of Electronic Science and Technology of China, Guangdong, 528402, China.
Jingzhou PanCollege of Management and Economics, Tianjin University, Tianjin, 300072, China.
Ge WangManagement School, Tianjin Polytechnic University, Tianjin, 300387, China.
Jingan WangZhongshan Institute, University of Electronic Science and Technology of China, Guangdong, 528402, China.
Ta-Chia ChinSchool of Management, Hangzhou Dianzi University, 310018, Zhejiang, China.
Li-Chung ChangZhongshan Institute, University of Electronic Science and Technology of China, Guangdong, 528402, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

R&D professionals are the impetus behind technological innovation, and their competitiveness and capability drive the growth of a company. However, high-tech industries have a chronic shortage of such indispensable professionals. Accordingly, reducing R&D personnel turnover has become a major human resource management challenge facing innovative companies. This study combined importance-performance analysis (IPA) with the decision-making trial and evaluation laboratory (DEMATEL) method to propose an IPA-DEMATEL model. Establishing this model involved three steps. First, an IPA was conducted to measure the importance of and satisfaction gained from job satisfaction criteria. Second, the DEMATEL method was used to determine the causal relationships of and interactive influence among the criteria. Third, a criteria model was constructed to evaluate job satisfaction of high-tech R&D personnel. On the basis of the findings, managerial suggestions are proposed.

Indexed as

Job SatisfactionModels, StatisticalTechnologyHumansIndustryResearchSurveys and Questionnaires

Identifiers

PMID27139697
PMCPMC4854457

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.