ارتباط بین استراتژی تولید، تعیین معیار، اندازه گیری عملکرد و مهندسی مجدد فرآیند کسب و کار
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers & Industrial Engineering, Volume 57, Issue 3, October 2009, Pages 963–975
An empirical analysis is presented for researching linkages between manufacturing strategy, benchmarking, performance measurement (PM) and business process reengineering (BPR). Although the importance of these linkages has been described in conceptual literature, it has not been widely demonstrated empirically. The survey research was carried out in 73 medium and large-sized Slovenian manufacturing companies within the mechanical, electro-mechanical and electronic industries. The resulting data were subjected to reliability and validity analyses. Canonical correlation analysis was used to test six hypotheses. The results confirmed the need for a strategically-driven BPR approach and the positive impact of performance measurement on BPR performance.
Business process reengineering (BPR) remains a controversial approach. The current state of BPR could be best paraphrased by using the statement written by MacIntosh (2003, p. 329) that, “as the body of academic research on BPR has grown, a number of contentious issues have emerged”. The most critical articles on BPR were probably published in the organisational studies literature (e.g. Case, 1999 and Grint and Case, 1998) but there are also a lot of articles which favour BPR as a management intervention tool, appearing as an answer to continuous changes, customers’ demands and competition (Davenport and Short, 1990, Goel and Chen, 2008a, Goel and Chen, 2008b, Grover and Malhotra, 1997, Gunasekaran and Kobu, 2002, Hammer, 1990, Hammer, 2004, Hammer and Champy, 1993, Han and Kang, 2007, Loewenthal, 1994, Motwani et al., 1998, O’Neil and Sohal, 1999 and Short and Venkatraman, 1992). According to McCabe and Knights (2000) BPR has been continually adopted by the practitioner community. A number of studies exist concerning what exactly constitutes BPR, such as through examination of BPR definitions, discussions about BPR tools and techniques, the importance of information technology, BPR and total quality management co-existence, understanding reengineering challenges and organisational processes, exploring critical success factors and many other issues on BPR. In addition, previous research has discussed the importance of linkages between manufacturing strategy and BPR (Edwards and Peppard, 1994, Edwards and Peppard, 1998, O’Neil and Sohal, 1998, Sarkis et al., 1997, Tinnilä, 1995 and Zairi and Sinclair, 1995), benchmarking and BPR (Earl and Khan, 1994 and Richman and Koontz, 1993) and performance measurement that was already determined as a part of BPR or, at least, closely correlated to BPR, by their initiators: Hammer, 1990 and Davenport and Short, 1990. However, no previous study attempts to empirically demonstrate the relationship between BPR, performance measurement, manufacturing strategy and benchmarking (Carr & Pearson, 1999) appear to be available. As a consequence of the great success of the first survey research on BPR dimensions performed in Slovenian Companies, we decided to deepen our research and explore also the connections or linkages between the researched areas: BPR, manufacturing strategy, benchmarking and performance measurement. We realize the word “linkages” in the presented BPR context sounds very narrow, since we know how many critical areas, success factors or dimensions should be considered to achieve effective process reengineering. But performed survey research provided us with reliable and valid BPR, manufacturing strategy, benchmarking and performance measurement constructs, indicating the basic characteristics (with statistically based confirmation) of the particular areas, even if restricted to specific sectors and countries. The part of the above-mentioned survey, related to the development and validation of BPR variables, has already been published by International Journal of Production Research (Herzog et al., 2006 and Herzog et al., 2007). The deficiency of empirical research about BPR was also ascertained by the literature reviews for the period from 1999 to 2005, thus confirming the suitability and adequacy of the presented research. This article has been developed over the following sections. Section 2 presents a developed research framework and the main issues of BPR, based on literature review. Hypotheses have been generated in advance of the study, to be tested against the data collected. Section 3 describes the methodology, including variable measurement and the sampling and data collection procedures. Section 4 presents variable construction using PCA for validity, and Cronbach’s alpha for reliability. Newly developed variables are shown to be reliable and valid and, thus, adequate for canonical correlation analysis performance. Section 5 presents and discusses the results of descriptive statistics canonical correlation analysis. Finally, Section 6 the conclusions of this study are presented, along with suggestions for future research (Section 7).
نتیجه گیری انگلیسی
The main purpose of the presented research is to contribute to a better understanding of relationships between manufacturing strategies, benchmarking, performance measurement, and business process reengineering. In regard to the number of performed BPR projects and published papers, we could say that BPR is in the maturity stage now. Although the importance of linkages between manufacturing strategy, benchmarking, performance measurement and BPR has been discussed in conceptual literature and even some empirical surveys exists, there is a lack of relevant large-scale empirical studies about BPR. Existing empirical research has identified some important relationships for BPR (e.g. relationship between IT and BPR, the role of performance measurement in BPR), therefore, we have tried to take into consideration all BPR-related topics. In the narrower sense the research set out to answer the question as to whether or not there exists any relationship between benchmarking, manufacturing strategy, performance measurement and BPR. These questions were answered by testing hypotheses. The results showed that there exist statistically significant relationships between BPR and performance measurement and between manufacturing strategy and BPR. The presented results were, in some ways, expected and they confirmed the relationships indicated in conceptual literature. In the broader and more complex sense the performed analysis provides us also with a deeper and more detailed understanding of relations between BPR and performance measurement tested within the third hypothesis. Canonical loadings indicated that all seven performance measurement variables were significantly related to the canonical variate representing performance measurement practices, with the most heavily weighted being: quality, human resources and employee satisfaction, customer satisfaction and time. The canonical crossloadings indicated that the practices most strongly related to the performance measurement are project of BPR, together with the top management commitment, and levers/results. Since there has not been any empirical research regarding connections between BPR and PM performed before we could say that presented research is of great importance for practitioners and researchers. It encourages the practitioners to have consistent use of both management concepts together and provides reliable and valid measures to researchers. The empirical results support well established and documented connection between BPR and PM (Hammer, 1990, Davenport and Short, 1990, Dixon et al., 1990, Hayes, 1994 and Kuwaiti and Kay, 2000). Similarly the second hypothesis, stated in the null form, denying the existence of a relationship between manufacturing strategy and BPR, was rejected, while the results of the survey research indicated that there exists a strong and positive relationship between manufacturing strategy and BPR. For BPR practice, canonical variate is primarily composed of education and training, employee cooperation, teamwork and top management commitment. Based on the crossloading results, the dimensions most strongly related to manufacturing strategy are employee satisfaction and growth, followed by variety of products, and flexibility in meeting customer demands. Comparison of the survey research results with the current practice published in literature (Edwards and Peppard, 1994, Edwards and Peppard, 1998, Lockamy et al., 1997 and Tinnilä, 1995) indicates the unity of theory and practice. Therefore, a very important message can be concluded, especially for practitioners: BPR should always be performed in connection with manufacturing strategy or BPR should be used as a tool for achieving goals set within manufacturing strategy. There was, however, no statistically significant relationship between a set of benchmarking variables and BPR variables, between manufacturing strategy and performance measurement, between benchmarking and performance measurement, and between manufacturing strategy and BPR. Some of these results were not expected and are even contrary to conceptual literature. For example, it is interesting that existing literature favours the relationship between manufacturing strategy and performance measurement indicators (Slack & Lewis, 2002) but, on the other hand, the results of the survey research cannot confirm these linkages. The canonical correlation results mostly showed the positive correlations between stated areas, but the values (particularly the redundancy index) are not high enough to confirm a significantly important relationship. As the most important value of the presented paper, the existence of an empirically important relationship (strong and positive) between BPR and performance measurement, as well as a strong and positive relationship between manufacturing strategy and BPR, can be exposed. This empirically demonstrated finding could also be of great importance for practitioners, when performing BPR. BPR implementation should always be correlated with manufacturing strategy and performance measurement.