یک چارچوب مبتنی بر فرایند شبکه ای تحلیلی برای موفقیت مدیریت کیفیت جامع (TQM): ارزیابی آمادگی صنعت ساخت ترکیه
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|4296||2007||18 صفحه PDF||سفارش دهید||10020 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 105, Issue 1, January 2007, Pages 79–96
In this study, we have developed an analytic network process (ANP)-based framework to identify the level of impact of different factors on total quality management (TQM) implementation and to assess the readiness of the Turkish manufacturing industry to adopt TQM practices. ANP is a methodology recently introduced by Saaty for multiple criteria problems where there is feedback and interdependence among decision attributes and alternatives. We determined the factors that affect the level of implementation of TQM by doing literature searches and further refined those factors through a survey conducted among 250 large manufacturing companies in Turkey. We ended up with 32 factors. When we applied the model into large manufacturing companies zero defect and costly and long-term study turned out to be the most influential factors contrary to those of survey respondents’ quality improvement and higher revenue. The results of our decision model show that the Turkish manufacturing industry has a readiness level of 59.2% for implementing TQM. Model identifies a number of factors for successful application; therefore, an understanding of the critical factors would help managers to advance TQM implementation. Since there is feedback and interdependence among these factors, ANP proves to be an effective framework for assessing readiness to adopt TQM and facilitating TQM implementation.
In the early 1980s, consumers became more powerful and started to demand high-quality goods and services at reasonable prices. The globalization of trade has made high-quality low-cost products available throughout the world. These factors increased the pressure on companies around the world to improve their goods and services. Technologies and methodologies such as total quality management (TQM) have helped them do this (Wadsworth et al., 2002). In Turkey, manufacturing organizations represent a dynamic and important sector of the economy and they are aware of the importance to their survival of assuring quality in their products. A considerable number of organizations have tried to implement these practices and have failed to achieve much, while many others have implemented TQM with great success. The overwhelming volume of literature on TQM is primarily focused on the elements of TQM and the approaches taken to assure a successful implementation; however, less attention has been devoted to identify the critical success factors for the implementation of TQM program (Dayton, 2001). Black and Porter (1996) developed a model that identifies a set of critical factors of TQM, their relative importance and the interrelationships between each. Recently Conca et al. (2004) conducted a similar study to identify critical success factors of TQM and empirically tested with the answers of 108 ISO certified firms in Spain. Since these critical factors are interdependent and there is feedback among them we contend that our analytic network process (ANP)-based framework is an enhancement to earlier studies. Since the critical success factors of TQM have not been studied extensively throughout the world, it is the intention of this study to investigate these factors and identify the relative importance of each of them in a successful TQM implementation and measure the readiness of the Turkish manufacturing industry to adopt it. The approach in this paper is to use the ANP to investigate the degree to which TQM practices were adopted in the Turkish manufacturing industry and to identify the impact of different factors on successful TQM implementation. This industry is particularly appropriate for the study of the effectiveness of TQM program implementation since the majority of organizations that have implemented TQM consist of manufacturing companies in Turkey. ANP requires expert judgments to assess the relative importance of different factors with respect to each other. In our study these expert judgments were obtained via survey of 250 manufacturing companies in Turkey. ANP is a new methodology introduced by Saaty (2001b) that extends the analytic hierarchy process (AHP) for decision making to cases of dependence and feedback. As Wang et al. (2004) pointed out, more and more researchers are realizing that AHP is an important generic method and are applying it. Whereas, ANP is relatively new and there are few applications as of yet. Some examples of ANP applications include re-engineering, supply chain performance, logistics, quality function deployment, energy policy planning, project selection decisions, and performance measurement systems (Hamalainen and Seppalainen, 1986, Partovi and Corredoira, 2002, Sarkis and Talluri, 2002, Agarwal and Shankar, 2002, Partovi, 2001, Lee and Kim, 2000, Ashayeri et al., 1998, Meade and Sarkis, 1998, Sarkis, 1998, Sarkis, 1999, Sarkis, 2003 and Karpak and Bayazit, 2001; Saaty, 2001a and Saaty, 2001c). In this paper we developed a framework that facilitates finding the importance of different factors on TQM implementation. In addition, we applied ANP for the first time to assess the readiness of manufacturing industry in Turkey to adopt TQM based on the survey of 62 companies. Since constructing such a framework can best be approached by studying organizations that have implemented TQM, we have excluded the ones which stated that they did not implement TQM. The paper is organized into five sections and begins with a literature search for the factors affecting TQM implementation. The methodology of the study is explained in Section 3. Section 4 introduces an ANP-based framework which identifies the importance of different factors on TQM implementation and Turkish manufacturing industry readiness to implement TQM. The overall conclusion is given in Section 5.
نتیجه گیری انگلیسی
In this paper, we have developed a framework based on ANP to identify the degree of impact of factors affecting TQM implementation and investigated the readiness of the Turkish manufacturing industry to adopt TQM practices based on a survey carried out among 250 large manufacturing companies in Turkey. We used the ANP for decision making with dependence and feedback based on four major factors as mapped to Saaty's benefits, costs, opportunities, risk (BOCR) model. ANP is a new methodology that incorporates feedback and interdependent relationships among decision attributes and alternatives. It leads to fresh insights about issues. Since we included only manufacturing companies in our research, this study indicates manufacturing industry readiness to adopt TQM. Manufacturing companies have been and will continue to be, for a while, a mainstay of the economy in Turkey and hence our results are most likely a good indicator of Turkish industry readiness in general. Based on our model we found that in Turkish industry, conditions for implementing TQM were 59.2% favorable as opposed to not implementing TQM. In the literature, only a few studies addressed the TQM readiness of an industry (Arasli, 2002, Weeks et al., 1995 and Aksu, 2003). In a decision problem, decision-makers might intuitively feel that some factors are more important than others in affecting their final preference among alternatives. If there is some feedback and interdependency among the factors, an unimportant factor may turn out to be far more important than even the most intuitively important one. So, there needs to be a methodology like ANP to capture more realistic results. In our research, we have identified 32 factors affecting TQM implementation. Some of the factors initially stated by survey participants to be the most important ones were not, interestingly enough. Because of interdependencies among the factors others turned out to be more important in the decision model. For example, according to the survey respondents quality improvement and higher revenue were the most important factors. But our ANP model showed quality improvement to be the fourth most important factor with higher revenue one of the least important factors. On the contrary, in our analysis, due to inner and outer dependencies, zero defects and costly and long-term study came up as the most crucial ones in TQM implementation.