Initiatives and outcomes of quality management implementation across industries
ABSTRACT DOI: 10.1016/S0305-0483(03)00021-5 This paper sets out to explore the quality initiatives of various industries and examine the links between quality management implementation and quality outcomes. We use the scenario in Hong Kong as a first step in addressing these research inquiries. Using Black and Porter's instrument (Decision Sci. 27 (1996) 1) and the various perceived performance measures representing quality management implementation and quality outcomes respectively, we conducted a mail survey to collect data from over 1000 companies with operational quality management systems and received 304 valid responses for data analysis. Analysis of variance (ANOVA) was used to analyze the data and the results are consistent with our prediction that the differences in quality initiatives by industry types affect the levels of quality management implementation and quality outcomes in different industries. In particular, we found that significant contrast exists between public utilities/service industries and manufacturing/construction industries, with the former group having a higher level of quality management implementation and achieving better quality outcomes. The emphases that they placed on their quality management implementation also seem to differ. Implications of the results are discussed and suggestions for further research on quality management and implementation are offerred. Author name used in this publication: Kee-hung Lai Author name used in this publication: T. C. E. Cheng
Full-textDOI: · Available from: Kee-hung Lai, Aug 13, 2015
- SourceAvailable from: Xiaosong (David) Peng
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- "However, simply adopting best practices may not be a universally applicable solution to reach " excellence " or " world class " status. Recently, OS researchers have begun to look into the contingency factors that may affect the effectiveness of operations capabilities (Sousa and Voss, 2008), among which are industrial context (Lai and Cheng, 2003), national culture (Voss and Blackmon, 1996), firm size (Sila, 2007), and competitive priorities (Ketokivi and Schroeder, 2004a). "
ABSTRACT: Purpose – Examining the strategic contingency of plant improvement capability and innovation capability. Two forms of fit between the two capabilities and competitive priorities were empirically tested. Design/Methodology/Approach – Data collected from a sample of 238 manufacturing plants were used to test the hypotheses using regression. Findings – The results provide partial support for fit as mediation. However, there was no evidence supporting fit as moderation. We found that improvement capability and innovation capability are associated with different competitive priorities and also have varying impact on different operational performance dimensions. Research limitations/implications – There are two limitations to this research: only three operations management (OM) practices are included in each capability examined; somewhat limited measures of competitive priorities and operational performance.Originality/value – This study examines multiple forms of fit between competitive priorities and operations capabilities. The findings can inform managers to selectively implement OM practices for developing the needed operations capabilities given the chosen competitive priorities.International Journal of Operations & Production Management 02/2011; 31(5). DOI:10.1108/01443571111126292 · 1.13 Impact Factor
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- "Some widely cited surveys include Chaudhry et al. (2000); Murthy and Shrivastav (2000); Robinson (2001); Khond and Dabade (2004); Antony et al. (2004). Ho et al. (2001); Mehra et al. (2001); Taylor et al. (2003); Lai et al. (2003); Khanna et al. (2002); Heizer et al. (2004); Shrivastava et al. (2004); Mohanty et al. (2006); and Dahlgaard and Dahlgaard (2006); and conducted empirical studies with various objectives like implementation of TQM in less and more experienced firms of US, various critical factors affecting total quality management at the business unit level, literature available on total quality management and using the literature search, field expert, identifies the future role of TQM in businesses facing global markets. Authors also provided various models and checked their validity in the scenario of TQM. "
ABSTRACT: Purpose – The purpose of this paper is to analyze the various factors important for total quality management implementation in various manufacturing organizations and to assess their relevance for Indian manufacturing organizations. Design/methodology/approach – A literature review was conducted for important factors and a survey approach was used to collect relevant data from industries. Further data were used to establish a model. Findings – It is shown that customer focus must be the prime objective for various industries to achieve total quality management. All the factors must be used systematically to achieve total quality management (TQM) and it can be done efficiently by using a model having four phases to implement TQM. Originality/value – The paper will be useful for manufacturing as well as service industries that are in the starting phase of TQM implementation or have already failed to implement TQM at their works.TQM Journal 10/2009; 21(6):607-622. DOI:10.1108/17542730910995873
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- "189 –204 issn 1059-1478 ͉ 05 ͉ 1402 ͉ 189$1.25 © 2005 Production and Operations Management Society ing industry, and that QM practices seem to have little association with any performance measures in the construction industry. Lai and Cheng (2003) showed that differences in quality initiatives by industry type affect the levels of implementation of quality management and quality outcomes. As a whole, the studies have suggested that quality management tends to have mixed results when covaried with industry type (Samson and Terziovski 1999). "
ABSTRACT: DOI: 10.5555/ijop.2005.14.2.189 Much of the empirical research in the past two decades has suggested that quality management (QM) is context dependent. This research develops an empirical QM model in a technology-based sector—electronics manufacturing. Based on quantitative and qualitative investigations of 225 electronics firms in Hong Kong and the Pearl River Delta (PRD) region of China, a path analytic model is developed. The empirical model shows that a typical quality management system (QMS) in the electronics industry is composed of four major modules, namely leadership, cultural elements, operational support systems, and process management. These modules create a series of chain effects on organizational performance, rather than acting as parallel elements with an equal impact. By quantifying their effects on organizational performance and comparing the model to others in the literature, we identify those QM constructs that are context dependent. In electronics manufacturing, process management and customer focus are more important than other elements (e.g., cultural factors) for garnering business results. This study contributes to contingency theory and research by identifying the key constructs and their relationships in a competitive, volatile, and technology-based industry with complex supply networks. Author name used in this publication: Kee-hung LaiProduction and Operations Management 06/2009; DOI:10.1111/j.1937-5956.2005.tb00018.x · 1.76 Impact Factor