تولید انعطاف پذیر : تعریف و تجزیه و تحلیل روابط بین شایستگی، قابلیت و رضایت مشتری
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|3637||2003||19 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 8470 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
- تولید محتوا با مقالات ISI برای سایت یا وبلاگ شما
- تولید محتوا با مقالات ISI برای کتاب شما
- تولید محتوا با مقالات ISI برای نشریه یا رسانه شما
پیشنهاد می کنیم کیفیت محتوای سایت خود را با استفاده از منابع علمی، افزایش دهید.
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Operations Management, Volume 21, Issue 2, March 2003, Pages 173–191
Fast and dramatic changes in customer expectations, competition, and technology are creating an increasingly uncertain environment. To respond, manufacturers are seeking to enhance flexibility across the value chain. Manufacturing flexibility, a critical dimension of value chain flexibility, is the ability to produce a variety of products in the quantities that customers demand while maintaining high performance. It is strategically important for enhancing competitive position and winning customer orders. This research organizes literature on manufacturing flexibility and classifies it according to competence and capability theory. It describes a framework to explore the relationships among flexible competence (machine, labor, material handling, and routing flexibilities), flexible capability (volume flexibility and mix flexibility), and customer satisfaction. It develops valid and reliable instruments to measure the sub-dimensions of manufacturing flexibility, and it applies structural equation modeling to a large-scale sample (n=273). The results indicate strong, positive, and direct relationships between flexible manufacturing competence and volume flexibility and between flexible manufacturing competence and mix flexibility. Volume flexibility and mix flexibility have strong, positive, and direct relationships with customer satisfaction.
Manufacturers face an increasingly uncertain external environment as the rate of change in customer expectations, global competition, and technology accelerates (Huber, 1984, Skinner, 1985, Jaikumar, 1986, Doll and Vonderembse, 1991 and Germain et al., 2001). Researchers and manufacturing managers contend that flexibility is a strategic imperative that enables firms to cope with uncertainty (Gerwin, 1987 and Sethi and Sethi, 1990). Flexibility is the organization’s ability to meet an increasing variety of customer expectations without excessive costs, time, organizational disruptions, or performance losses. Upton, 1994 and Upton, 1995 defines flexibility as increasing the range of products available, improving a firm’s ability to respond quickly, and achieving good performance over this wide range of products. To attain the type of flexibility that customers want (i.e. quick delivery of a variety of high-quality, low-cost products), organizations seek value chain flexibility (Zhang, 2001). Value chain flexibility is broadly defined to include product development, manufacturing, logistics, and spanning flexibilities (Zhang, 2001 and Day, 1994). It focuses primarily on filling customer orders rather than on merely improving the efficiency and effectiveness of equipment and processes. Such a focus requires manufacturing firms to develop cross-functional and cross-company efforts that eliminate bottlenecks, increase responsiveness, and create a level of performance that enables firms to build competitive advantage (Blackburn, 1991 and Hamel and Prahalad, 1989). Manufacturing flexibility, the focus of this study, is the ability of the firm to manage production resources and uncertainty to meet customer requests (Behrbohm, 1985, Gerwin, 1993, Kathuria and Partovi, 1999, Hill, 1994, D’Souza and Williams, 2000 and Koste and Malhotra, 1999). Sethi and Sethi (1990) contend that manufacturing flexibility is a hard-to-capture concept, and Upton (1995) believes that confusion and ambiguity about this concept inhibit its effective management. Slack, 1983 and Slack, 1987 distinguishes resource flexibility (e.g., machine flexibility) from systems flexibility (e.g., mix flexibility). Correa and Slack (1996) define the attributes of systems flexibility (range and response) and types of systems flexibility (e.g. product mix and production volume). Different descriptors for manufacturing flexibility overlap; as an example, process flexibility intersects with operational flexibility. Some descriptors are aggregates of others; process flexibility includes routing flexibility, machine flexibility, and material handling flexibility. The concept of manufacturing flexibility is confounded because the attributes of flexibility (i.e. range, mobility, and uniformity) and the components of flexibility (e.g. machine flexibility and volume flexibility) are often mingled (Barad, 1992, Gupta, 1993 and Benjaafar, 1994). This imprecise language makes it difficult to develop valid and reliable measures of manufacturing flexibility and to improve theory development. Clear definitions and accurate measures are needed to construct and test theory related to manufacturing flexibility. The literature on this important subject is accumulating including case studies (Maffei and Meredith, 1995), industry specific studies (Suarez et al., 1996), and mathematical models (Kumar, 1987, Benjaafar and Ramakrishnan, 1996, Gupta, 1993, Jordan and Graves, 1995 and Byrne and Chutima, 1997). Upton, 1995 and Upton, 1997) provides a measure of process range based on a small sample survey (54 plants). Suarez et al., 1995 and Suarez et al., 1996 offer a measure of flexibility on the printed circuit board industry. Gupta and Somers (1992) develop measures of manufacturing flexibility based on a large-scale survey, but they do not clearly describe the dimensions underlying each type of manufacturing flexibility. Some researchers emphasize manufacturing flexibility as an internal resource, a competence (Carter, 1986 and Das and Nagendra, 1993). They highlight task sequencing or dispatching disciplines, and they develop flexible machining systems with totally automated functions to cope with uncertainty. But flexible systems that focus on creating internal competencies (e.g. routing flexibility and machine flexibility) may not enhance customer satisfaction. Satisfaction increases as the firm builds capabilities (e.g. mix flexibility) that provide value to customers. To understand manufacturing flexibility, the internal competencies and external capabilities of flexibility should be clarified, and relationships between them should be examined. This paper contributes to the manufacturing literature by: (1) delineating manufacturing flexibility into dimensions of flexible manufacturing competence (machine, labor, material handling, and routing flexibilities) and flexible manufacturing capability (volume flexibility and mix flexibility), (2) proposing a research framework, including hypotheses, that relates competence to capability and capability to customer satisfaction, (3) developing valid and reliable measures for the dimensions of competence and capability, and (4) testing the hypotheses described in the framework using structural equations modeling. The results and implications of our findings are also discussed.
نتیجه گیری انگلیسی
This paper describes manufacturing flexibility as an integral part of value chain flexibility and discusses its key sub-dimensions. It provides theoretical justification for a research model that relates flexible manufacturing competencies, volume flexibility, mix flexibility, and customer satisfaction. Based on the extensive literature review, the concept and sub-dimensions of manufacturing flexibility have been defined and clarified including three distinctive attributes: range, mobility, and uniformity. This study applies competence and capability theory to this issue, which brings a systematic, resource-based view of manufacturing flexibility. By building a network of manufacturing flexibility constructs and conducting analysis across a large number of organizations, this study represents an initial investigation of manufacturing flexibility rooted in a comprehensive view of value chain flexibility. It points out and empirically confirms that flexible manufacturing competencies support the firm’s flexible capabilities, i.e. volume flexibility and mix flexibility. These flexible capabilities, in turn, enhance customer satisfaction. This paper also develops a set of valid and reliable instruments to measure the sub-dimensions of manufacturing flexibility. These instruments were developed through a carefully designed large-scale data collection process that used rigorous instrument development methods. The final instruments, listed in Appendix A, are short and easy to use. Each scale has six or fewer items and the total number of items across six scales is only 32. The content domains of the constructs were adequately covered because care was taken during item generation and evaluation. The factor structure is simple and has good loadings. The instruments exceed generally accepted validity and reliability standards for basic research. These scales represent substantial progress towards the establishment of standard instruments for measuring manufacturing flexibility, and they have several applications in practice. They can be used to evaluate manufacturing flexibility in an organization. In addition to an overall assessment, they can be used to target specific aspects of manufacturing flexibility and to determine where problems may exist. These instruments can also be used to compare manufacturing flexibility among various divisions of the same company or to compare it across organizations. The results of these comparisons can lead to new approaches to manufacturing and business strategies. It is important to recognize that a single study does not provide valid measures in the true spirit of instrument developments. This study, through successive stages of analysis and refinement, has arrived at a final list of operational indicators that satisfied important reliability and validity criteria. Such a list should be replicated and refined in other research contexts. Given the perceptual nature of the data used to assess the theoretical constructs, it is important to recognize problems associated with the key informant approach. Although the use of one respondent per participating company has the possibility of mono-respondent bias and common methods variance, it is necessary to arrive at a list of acceptable indicators before proceeding to examine inter-informant consistency. Future studies should collect new data to confirm both the manufacturing flexibility measures and the structural model results. This would provide further evidence for the validity and reliability of the instruments, and it would speed the diffusion of standard instruments among the academic community. Future research may include similar studies for other aspects of value chain flexibility: product development, logistic, and spanning flexibilities. It may also examine relationships among the four dimensions of value chain flexibility.