International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Most Trusted Research Journal Since Year 2012

ISSN: 2319-7064



Research Paper | Management | Malaysia | Volume 3 Issue 6, June 2014

Predictors of Union Commitment among the Public Sector Employees

Husna Johari

Based on the dramatic changes taking place such as globalization; technological advancement and change in work structure have in reality exert some pressure on the movement of trade union around the globe. Previously; in the Malaysian context; the government has introduced some major plans. These include The Government Transformation Program (GTP) and Economic Transformation Program (ETP) as the key components of National Transformation Program (NTP). The transformation programs have brought in new changes to employment sector that has lead to drastic changes in public and private sector administration. Despite all the efforts introduced; the landscape of trade union movement remains unchanged in certain aspects. Hence; this study explored factors that may predict members commitment toward their unions. A survey questionnaire was employed and data was collected from a random sample of 395 members. Based on regression analysis; the results generally showed strong relationship between the factors and union commitment dimensions which resulted in partial acceptance of the hypotheses formulated. Factors like general union beliefs; union satisfaction; and union leadership significantly influenced the value union commitment dimension; while only union instrumentality influenced instrumental union commitment dimension. From the research findings; some implications are discussed. Limitation and suggestions for future research were also highlighted.

Keywords: union commitment, public, private, sector

Edition: Volume 3 Issue 6, June 2014

Pages: 2515 - 2521


How to Cite this Article?

Husna Johari, "Predictors of Union Commitment among the Public Sector Employees", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=2014597, Volume 3 Issue 6, June 2014, 2515 - 2521

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Singer identification is one of the most important applications of Music Information Retrieval (MIR). The process starts with identifying first, the audio descriptors then using these feature vectors, as input, for further classification/ identification of singers using typical classifiers, such as Gaussian Mixture Model (GMM) or Hidden Markov Model (HMM). In this paper, we propose, a Hybrid method of selecting correct audio descriptors for the identification of singer of Indian Classical Music. First, only strong (primary) audio descriptors are released on the system in forward pass and the classification impact is recorded. Then only selecting the top few audio descriptors, having largest impact on the singer identification process, are selected and rest are eliminated in the backward pass. Then selecting and releasing all the less significant audio descriptors from the groups, that had maximum impact on singer identification process, increases the success of correctly identifying the singer. The method reduces substantially the large number of audio descriptors to few, important audio descriptors. The selected audio descriptors are then fed as input to further classifiers.