International Journal of Quality ScienceTable of Contents for International Journal of Quality Science. List of articles from the current issue, including Just Accepted (EarlyCite)https://www.emerald.com/insight/publication/issn/1359-8538/vol/3/iss/4?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestInternational Journal of Quality ScienceEmerald Publishing LimitedInternational Journal of Quality ScienceInternational Journal of Quality Sciencehttps://www.emerald.com/insight/proxy/containerImg?link=/resource/publication/journal/75cc7c21196106c7cadb3ce81bbe67ba/UNKNOWNhttps://www.emerald.com/insight/publication/issn/1359-8538/vol/3/iss/4?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestAn empirical investigation into methods affecting the quality of new product innovationshttps://www.emerald.com/insight/content/doi/10.1108/13598539810243595/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestSeventy‐five new product development projects were studied in ten large companies to test potential strategic and process antecedents to quality. Seven factors were found to significantly increase product quality: high importance placed on quality by top management, high reward for process speed, high project stream breadth, high use of internal (versus external) sources of ideas and technology, low overlap or concurrency of the development process, low turfguarding or “silo” orientation, and high development milestone frequency. These results suggest that managers need to pay attention to both strategic orientation factors and structure‐related organizational capability factors to increase product quality. Staffing‐related factors did not seem to have a strong impact on quality; this suggests that quality is more a function of systemic versus individual factors. Additionally, it was found that there were some differences in the factors associated with high‐quality products between radical and incremental innovations. However, the study is exploratory and further research needs to test these findings as well as extend them to include other interrelationships between factors.An empirical investigation into methods affecting the quality of new product innovations
Eric H. Kessler, Alok K. Chakrabarti
International Journal of Quality Science, Vol. 3, No. 4, pp.302-319
Seventy‐five new product development projects were studied in ten large companies to test potential strategic and process antecedents to quality. Seven factors were found to significantly increase product quality: high importance placed on quality by top management, high reward for process speed, high project stream breadth, high use of internal (versus external) sources of ideas and technology, low overlap or concurrency of the development process, low turfguarding or “silo” orientation, and high development milestone frequency. These results suggest that managers need to pay attention to both strategic orientation factors and structure‐related organizational capability factors to increase product quality. Staffing‐related factors did not seem to have a strong impact on quality; this suggests that quality is more a function of systemic versus individual factors. Additionally, it was found that there were some differences in the factors associated with high‐quality products between radical and incremental innovations. However, the study is exploratory and further research needs to test these findings as well as extend them to include other interrelationships between factors.]]>
An empirical investigation into methods affecting the quality of new product innovations10.1108/13598539810243595International Journal of Quality Science1998-12-01© 1998 Eric H. KesslerAlok K. ChakrabartiInternational Journal of Quality Science341998-12-0110.1108/13598539810243595https://www.emerald.com/insight/content/doi/10.1108/13598539810243595/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1998
Application of data envelop analysis in benchmarkinghttps://www.emerald.com/insight/content/doi/10.1108/13598539810243603/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestIn 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.Application of data envelop analysis in benchmarking
Christian N. Madu, Chu‐Hua Kuei
International Journal of Quality Science, Vol. 3, No. 4, pp.320-327
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.]]>
Application of data envelop analysis in benchmarking10.1108/13598539810243603International Journal of Quality Science1998-12-01© 1998 Christian N. MaduChu‐Hua KueiInternational Journal of Quality Science341998-12-0110.1108/13598539810243603https://www.emerald.com/insight/content/doi/10.1108/13598539810243603/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1998
Strategic approaches, organizational design and quality managementhttps://www.emerald.com/insight/content/doi/10.1108/13598539810243667/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThe main contribution of this paper is to integrate into one model management and organizational fields that are normally analyzed separately: contingency factors, organizational design variables, strategic approaches and quality management approaches. The essential core of the model is constituted by three basic variables of organizational design: level of centralization, level of formalization‐standardization, and level of shared vision and common values. Through analysis using this conceptual tool, we can: assess the position of tasks and organizational units in relation to these organizational variables; evaluate the congruence between organizational variables and contingency factors; identify relationships between strategic management approaches and quality approaches; and establish a fit between strategic management approaches, organizational variables, contingency factors and quality approaches.Strategic approaches, organizational design and quality management
Moreno‐Luzón, F.J. Peris
International Journal of Quality Science, Vol. 3, No. 4, pp.328-347
The main contribution of this paper is to integrate into one model management and organizational fields that are normally analyzed separately: contingency factors, organizational design variables, strategic approaches and quality management approaches. The essential core of the model is constituted by three basic variables of organizational design: level of centralization, level of formalization‐standardization, and level of shared vision and common values. Through analysis using this conceptual tool, we can: assess the position of tasks and organizational units in relation to these organizational variables; evaluate the congruence between organizational variables and contingency factors; identify relationships between strategic management approaches and quality approaches; and establish a fit between strategic management approaches, organizational variables, contingency factors and quality approaches.]]>
Strategic approaches, organizational design and quality management10.1108/13598539810243667International Journal of Quality Science1998-12-01© 1998 Moreno‐LuzónF.J. PerisInternational Journal of Quality Science341998-12-0110.1108/13598539810243667https://www.emerald.com/insight/content/doi/10.1108/13598539810243667/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1998
An empirical assessment of quality: research considerationshttps://www.emerald.com/insight/content/doi/10.1108/13598539810243630/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThis paper examines research design issues in quality management studies. Potential research problems are identified and suggestions provided on how these problems could be addressed through effective research design techniques. A good research design enables the researcher to address the right questions and to provide meaningful recommendations. The emphasis of this paper is on empirical research in total quality management. Empirical studies are now common in validating some of the claims associated with quality, especially its association with organizational performance. However, conclusions on tests conducted on quality hypotheses are as good as the research design. Therefore, empirical researchers in the quality management field need to focus more attention on their research design and methodology to ensure that their conclusions are indeed a reflection of their hypotheses.An empirical assessment of quality: research considerations
Christian N. Madu
International Journal of Quality Science, Vol. 3, No. 4, pp.348-355
This paper examines research design issues in quality management studies. Potential research problems are identified and suggestions provided on how these problems could be addressed through effective research design techniques. A good research design enables the researcher to address the right questions and to provide meaningful recommendations. The emphasis of this paper is on empirical research in total quality management. Empirical studies are now common in validating some of the claims associated with quality, especially its association with organizational performance. However, conclusions on tests conducted on quality hypotheses are as good as the research design. Therefore, empirical researchers in the quality management field need to focus more attention on their research design and methodology to ensure that their conclusions are indeed a reflection of their hypotheses.]]>
An empirical assessment of quality: research considerations10.1108/13598539810243630International Journal of Quality Science1998-12-01© 1998 Christian N. MaduInternational Journal of Quality Science341998-12-0110.1108/13598539810243630https://www.emerald.com/insight/content/doi/10.1108/13598539810243630/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1998
Comparing tools for service quality evaluationhttps://www.emerald.com/insight/content/doi/10.1108/13598539810243658/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestService quality evaluation is one of the main issues that have recently drawn managers’ and researchers’ attention. The definition of an evaluation standard not dependent on any particular service context has determined the popularity of many different quality tools. In this paper we show a comparative analysis of the affected tools that are widely used. These are summarized in an orientation map. Moreover we present some results of an experiment carried out with two of the major quality tools (SERVQUAL and QUALITOMETRO). The results identify good qualities as well as weaknesses for both tools. Possible improvement strategies are presented.Comparing tools for service quality evaluation
Fiorenzo Franceschini, Marco Cignetti, Mara Caldara
International Journal of Quality Science, Vol. 3, No. 4, pp.356-367
Service quality evaluation is one of the main issues that have recently drawn managers’ and researchers’ attention. The definition of an evaluation standard not dependent on any particular service context has determined the popularity of many different quality tools. In this paper we show a comparative analysis of the affected tools that are widely used. These are summarized in an orientation map. Moreover we present some results of an experiment carried out with two of the major quality tools (SERVQUAL and QUALITOMETRO). The results identify good qualities as well as weaknesses for both tools. Possible improvement strategies are presented.]]>
Comparing tools for service quality evaluation10.1108/13598539810243658International Journal of Quality Science1998-12-01© 1998 Fiorenzo FranceschiniMarco CignettiMara CaldaraInternational Journal of Quality Science341998-12-0110.1108/13598539810243658https://www.emerald.com/insight/content/doi/10.1108/13598539810243658/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1998
QUALITY CORNERhttps://www.emerald.com/insight/content/doi/10.1108/13598539810243676/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestCompanies of all types are investing significant time and resources in regularly “assessing” themselves according to an internally designed set of criteria. More and more, these assessments are focused broadly on entire company systems and less on pure quality criteria, such as the quality of products and services. Although each firm strives to find the “right” set of criteria for their unique position, set of circumstances, and idiosyncratic culture, most seem to gravitate toward a set of loosely defined, generic characteristics which, to a remarkable extent, reflect the broad categories of the Malcolm Baldrige National Quality Award Criteria. This article examines the linkages between broadly defined assessment criteria and the comprehensive structure of the Malcolm Baldrige National Quality Award.QUALITY CORNER
J. Michael Reames
International Journal of Quality Science, Vol. 3, No. 4, pp.368-375
Companies of all types are investing significant time and resources in regularly “assessing” themselves according to an internally designed set of criteria. More and more, these assessments are focused broadly on entire company systems and less on pure quality criteria, such as the quality of products and services. Although each firm strives to find the “right” set of criteria for their unique position, set of circumstances, and idiosyncratic culture, most seem to gravitate toward a set of loosely defined, generic characteristics which, to a remarkable extent, reflect the broad categories of the Malcolm Baldrige National Quality Award Criteria. This article examines the linkages between broadly defined assessment criteria and the comprehensive structure of the Malcolm Baldrige National Quality Award.]]>
QUALITY CORNER10.1108/13598539810243676International Journal of Quality Science1998-12-01© 1998 J. Michael ReamesInternational Journal of Quality Science341998-12-0110.1108/13598539810243676https://www.emerald.com/insight/content/doi/10.1108/13598539810243676/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1998