{"title":"数据包络分析在基准测试中的应用","authors":"C. Madu, C. Kuei","doi":"10.1108/13598539810243603","DOIUrl":null,"url":null,"abstract":"In this paper, we demonstrate how data envelopment analysis (DEA) could be used in benchmarking studies. Our study is based on an empirical survey of small family‐owned businesses. This survey identified the separating variables between “high performing” and “low performing” firms in improving organizational performance through quality management. However, it did not suggest how “low performers” can transform to “high performers”. In the present study, we demonstrate this transformation by specifically showing how inefficient companies can become more efficient. This is done by identifying a company or composite companies that an inefficient firm needs to benchmark on a specific quality instrument. The current study will make empirical surveys more functional to industrial practitioners. It is more important to show how companies can continuously improve their processes than to classify them as “high” or “low” performers.","PeriodicalId":376191,"journal":{"name":"International Journal of Quality Science","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1998-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Application of data envelop analysis in benchmarking\",\"authors\":\"C. Madu, C. Kuei\",\"doi\":\"10.1108/13598539810243603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we demonstrate how data envelopment analysis (DEA) could be used in benchmarking studies. Our study is based on an empirical survey of small family‐owned businesses. This survey identified the separating variables between “high performing” and “low performing” firms in improving organizational performance through quality management. However, it did not suggest how “low performers” can transform to “high performers”. In the present study, we demonstrate this transformation by specifically showing how inefficient companies can become more efficient. This is done by identifying a company or composite companies that an inefficient firm needs to benchmark on a specific quality instrument. The current study will make empirical surveys more functional to industrial practitioners. It is more important to show how companies can continuously improve their processes than to classify them as “high” or “low” performers.\",\"PeriodicalId\":376191,\"journal\":{\"name\":\"International Journal of Quality Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Quality Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/13598539810243603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Quality Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/13598539810243603","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of data envelop analysis in benchmarking
In this paper, we demonstrate how data envelopment analysis (DEA) could be used in benchmarking studies. Our study is based on an empirical survey of small family‐owned businesses. This survey identified the separating variables between “high performing” and “low performing” firms in improving organizational performance through quality management. However, it did not suggest how “low performers” can transform to “high performers”. In the present study, we demonstrate this transformation by specifically showing how inefficient companies can become more efficient. This is done by identifying a company or composite companies that an inefficient firm needs to benchmark on a specific quality instrument. The current study will make empirical surveys more functional to industrial practitioners. It is more important to show how companies can continuously improve their processes than to classify them as “high” or “low” performers.