Pub Date : 2023-09-14DOI: 10.1108/ijqrm-03-2023-0076
Julia T. Thomas, Mahesh Kumar
Purpose The purpose of the paper is set to minimize the total cost of a manufacturing system when an acceptance sampling plan (ASP) is carried out in a fuzzy environment. Design/methodology/approach A fuzzy acceptance sampling plan (FASP) is employed for the inspection of the batch of products and a fuzzy cost optimization problem is formulated. Findings The extent of uncertainty determines an interval for the total cost function with upper and lower bounds. The effect of variation in the ambiguity of the proportion of defectives in the probability of acceptance is determined. Practical implications The proposed model is specifically designed for production and supply units with ASP for attributes. Still, the proportion of defectives in the inspection process is fuzzy. Originality/value Fuzzy probability distribution is used to model an optimal inspection plan for a general supply chain. Economic design of supply chain under fuzzy proportion of defectives is discussed for the first time.
{"title":"Cost optimization of acceptance sampling plan in a fuzzy supply chain environment","authors":"Julia T. Thomas, Mahesh Kumar","doi":"10.1108/ijqrm-03-2023-0076","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2023-0076","url":null,"abstract":"Purpose The purpose of the paper is set to minimize the total cost of a manufacturing system when an acceptance sampling plan (ASP) is carried out in a fuzzy environment. Design/methodology/approach A fuzzy acceptance sampling plan (FASP) is employed for the inspection of the batch of products and a fuzzy cost optimization problem is formulated. Findings The extent of uncertainty determines an interval for the total cost function with upper and lower bounds. The effect of variation in the ambiguity of the proportion of defectives in the probability of acceptance is determined. Practical implications The proposed model is specifically designed for production and supply units with ASP for attributes. Still, the proportion of defectives in the inspection process is fuzzy. Originality/value Fuzzy probability distribution is used to model an optimal inspection plan for a general supply chain. Economic design of supply chain under fuzzy proportion of defectives is discussed for the first time.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135488756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-14DOI: 10.1108/ijqrm-07-2021-0215
Xenia J. Mamakou, Panagiotis Zaharias, Maria Milesi
Purpose The purpose of this study is to explore the interplay between electronic service quality, user experience (UX) and overall customer satisfaction. Additionally, it aims to assess the suitability of E-S-QUAL and UX metrics within the cultural context of Greece. Design/methodology/approach Data were collected from 310 Internet users based on their last online purchase from an e-retail website. To evaluate the conceptual model, the authors used partial least squares structural equation modeling (PLS-SEM). Findings The findings of this study validate the scales' reliability and validity in the realm of electronic commerce (e-commerce) in Greece. The findings also emphasize the favorable association between e-service quality and UX with overall satisfaction, while indicating that e-service quality plays a partial mediating role in the relationship between UX and customer satisfaction. Originality/value The authors' study enhances the existing theory by introducing a new multi-dimensional conceptual framework that illuminates the relative importance of the dimensions within the scales. Additionally, it offers valuable insights into the impacts of e-service quality and UX on overall satisfaction, providing managers and practitioners with a tool to evaluate the quality of their electronic services and make necessary adjustments to meet the needs of their customers.
{"title":"Measuring customer satisfaction in electronic commerce: the impact of e-service quality and user experience","authors":"Xenia J. Mamakou, Panagiotis Zaharias, Maria Milesi","doi":"10.1108/ijqrm-07-2021-0215","DOIUrl":"https://doi.org/10.1108/ijqrm-07-2021-0215","url":null,"abstract":"Purpose The purpose of this study is to explore the interplay between electronic service quality, user experience (UX) and overall customer satisfaction. Additionally, it aims to assess the suitability of E-S-QUAL and UX metrics within the cultural context of Greece. Design/methodology/approach Data were collected from 310 Internet users based on their last online purchase from an e-retail website. To evaluate the conceptual model, the authors used partial least squares structural equation modeling (PLS-SEM). Findings The findings of this study validate the scales' reliability and validity in the realm of electronic commerce (e-commerce) in Greece. The findings also emphasize the favorable association between e-service quality and UX with overall satisfaction, while indicating that e-service quality plays a partial mediating role in the relationship between UX and customer satisfaction. Originality/value The authors' study enhances the existing theory by introducing a new multi-dimensional conceptual framework that illuminates the relative importance of the dimensions within the scales. Additionally, it offers valuable insights into the impacts of e-service quality and UX on overall satisfaction, providing managers and practitioners with a tool to evaluate the quality of their electronic services and make necessary adjustments to meet the needs of their customers.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135490867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.1108/ijqrm-12-2022-0353
Ying Yang, Biao Yang
Purpose This study emphasises the importance of employee participation in total productive maintenance and identifies the key factors influencing employee participation. The Motivation-Opportunity-Ability (MOA) framework is adopted to identify and categorise key factors. Design/methodology/approach An embedded case study with a power plant service provider in England was conducted with a variety of research methods, for example interviews and questionnaire surveys, to gain a wide range of data. Findings Following the MOA framework, this study shows various key aspects of employees' motivation, opportunity and ability when participating in total productive maintenance. It also compares first-line machine operators and maintenance specialists in terms of the drivers and barriers to total productive maintenance for them, and reveals that they need different mechanical skills in order to participate in total productive maintenance. Originality/value The study extends the applications of the MOA framework to total productive maintenance initiatives and provides managers with guidance on how to correctly consider and prioritise employee participation in their implementation. Moreover, this is the first study to identify differences between first-line machine operators and maintenance specialists, in terms of their willingness to participate in total productive maintenance.
{"title":"Employee participation in total productive maintenance – a bottom-up perspective","authors":"Ying Yang, Biao Yang","doi":"10.1108/ijqrm-12-2022-0353","DOIUrl":"https://doi.org/10.1108/ijqrm-12-2022-0353","url":null,"abstract":"Purpose This study emphasises the importance of employee participation in total productive maintenance and identifies the key factors influencing employee participation. The Motivation-Opportunity-Ability (MOA) framework is adopted to identify and categorise key factors. Design/methodology/approach An embedded case study with a power plant service provider in England was conducted with a variety of research methods, for example interviews and questionnaire surveys, to gain a wide range of data. Findings Following the MOA framework, this study shows various key aspects of employees' motivation, opportunity and ability when participating in total productive maintenance. It also compares first-line machine operators and maintenance specialists in terms of the drivers and barriers to total productive maintenance for them, and reveals that they need different mechanical skills in order to participate in total productive maintenance. Originality/value The study extends the applications of the MOA framework to total productive maintenance initiatives and provides managers with guidance on how to correctly consider and prioritise employee participation in their implementation. Moreover, this is the first study to identify differences between first-line machine operators and maintenance specialists, in terms of their willingness to participate in total productive maintenance.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135394854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1108/ijqrm-06-2022-0183
Pratik Ghosh, Deepika Jhamb, Rahul Dhiman
Purpose The aim of the paper is to measure the service quality, satisfaction, service value and behavioral intentions of Gen Z in leading global Quick Service Restaurants (QSRs) in India by integrating QUICKSERV into an established model of consumer behavior. Design/methodology/approach A cross-sectional study design was used for the hypothesis testing. Service quality perceptions with satisfaction, service value and behavioral intentions were measured using structural equation modeling. Findings The outcomes suggest a direct effect of the service quality of QSRs on the satisfaction, service value and behavioral intentions of Gen Z customers. Satisfaction further influenced customers' behavioral intentions. However, customer satisfaction and behavioral intentions were not directly influenced by service value. Finally, the association between service quality and behavioral intentions was mediated by satisfaction. Practical implications Managers should encourage a pleasant attitude, good grooming and friendliness in QSR employees as Gen Z highly values these aspects. At the same time, QSRs should focus to elevate the service value of Gen Z customers by lowering their sacrifice perceptions and fostering initiatives. Originality/value Although many studies have considered millennials along with Gen Z to analyze the relationship between service quality and behavioral intentions in different service settings, few researchers have considered the impact of Gen Z consumer features in service quality research separately. The findings of the study will help both practitioners of different QSR brands and facilitators in hospitality academia to better understand the nuances and uniqueness of Gen Z consumer behavior in the QSRs.
{"title":"Measuring QSR service quality on behavioral intentions of gen Z customers using QUICKSERV–mediating effect of service value and satisfaction","authors":"Pratik Ghosh, Deepika Jhamb, Rahul Dhiman","doi":"10.1108/ijqrm-06-2022-0183","DOIUrl":"https://doi.org/10.1108/ijqrm-06-2022-0183","url":null,"abstract":"Purpose The aim of the paper is to measure the service quality, satisfaction, service value and behavioral intentions of Gen Z in leading global Quick Service Restaurants (QSRs) in India by integrating QUICKSERV into an established model of consumer behavior. Design/methodology/approach A cross-sectional study design was used for the hypothesis testing. Service quality perceptions with satisfaction, service value and behavioral intentions were measured using structural equation modeling. Findings The outcomes suggest a direct effect of the service quality of QSRs on the satisfaction, service value and behavioral intentions of Gen Z customers. Satisfaction further influenced customers' behavioral intentions. However, customer satisfaction and behavioral intentions were not directly influenced by service value. Finally, the association between service quality and behavioral intentions was mediated by satisfaction. Practical implications Managers should encourage a pleasant attitude, good grooming and friendliness in QSR employees as Gen Z highly values these aspects. At the same time, QSRs should focus to elevate the service value of Gen Z customers by lowering their sacrifice perceptions and fostering initiatives. Originality/value Although many studies have considered millennials along with Gen Z to analyze the relationship between service quality and behavioral intentions in different service settings, few researchers have considered the impact of Gen Z consumer features in service quality research separately. The findings of the study will help both practitioners of different QSR brands and facilitators in hospitality academia to better understand the nuances and uniqueness of Gen Z consumer behavior in the QSRs.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":"286 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135583265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-11DOI: 10.3390/brainsci12050630
Wei Liu, Kebin Jia, Zhuozheng Wang, Zhuo Ma
Depression has gradually become the most common mental disorder in the world. The accuracy of its diagnosis may be affected by many factors, while the primary diagnosis seems to be difficult to define. Finding a way to identify depression by satisfying both objective and effective conditions is an urgent issue. In this paper, a strategy for predicting depression based on spatiotemporal features is proposed, and is expected to be used in the auxiliary diagnosis of depression. Firstly, electroencephalogram (EEG) signals were denoised through the filter to obtain the power spectra of the three corresponding frequency ranges, Theta, Alpha and Beta. Using orthogonal projection, the spatial positions of the electrodes were mapped to the brainpower spectrum, thereby obtaining three brain maps with spatial information. Then, the three brain maps were superimposed on a new brain map with frequency domain and spatial characteristics. A Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) were applied to extract the sequential feature. The proposed strategy was validated with a public EEG dataset, achieving an accuracy of 89.63% and an accuracy of 88.56% with the private dataset. The network had less complexity with only six layers. The results show that our strategy is credible, less complex and useful in predicting depression using EEG signals.
{"title":"A Depression Prediction Algorithm Based on Spatiotemporal Feature of EEG Signal.","authors":"Wei Liu, Kebin Jia, Zhuozheng Wang, Zhuo Ma","doi":"10.3390/brainsci12050630","DOIUrl":"10.3390/brainsci12050630","url":null,"abstract":"<p><p>Depression has gradually become the most common mental disorder in the world. The accuracy of its diagnosis may be affected by many factors, while the primary diagnosis seems to be difficult to define. Finding a way to identify depression by satisfying both objective and effective conditions is an urgent issue. In this paper, a strategy for predicting depression based on spatiotemporal features is proposed, and is expected to be used in the auxiliary diagnosis of depression. Firstly, electroencephalogram (EEG) signals were denoised through the filter to obtain the power spectra of the three corresponding frequency ranges, Theta, Alpha and Beta. Using orthogonal projection, the spatial positions of the electrodes were mapped to the brainpower spectrum, thereby obtaining three brain maps with spatial information. Then, the three brain maps were superimposed on a new brain map with frequency domain and spatial characteristics. A Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) were applied to extract the sequential feature. The proposed strategy was validated with a public EEG dataset, achieving an accuracy of 89.63% and an accuracy of 88.56% with the private dataset. The network had less complexity with only six layers. The results show that our strategy is credible, less complex and useful in predicting depression using EEG signals.</p>","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":"20 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9139403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84392165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-22DOI: 10.1108/ijqrm-03-2022-414
M. Ram, C. Madu, L. Xing, T. Dohi
{"title":"Guest editorial: Recent communications in system reliability, quality and supply chain management","authors":"M. Ram, C. Madu, L. Xing, T. Dohi","doi":"10.1108/ijqrm-03-2022-414","DOIUrl":"https://doi.org/10.1108/ijqrm-03-2022-414","url":null,"abstract":"","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43169556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-08DOI: 10.1108/ijqrm-08-2021-0298
Ritu Gupta, Zainab Tasneem
PurposeThe purpose of this study is to develop Markovian model to obtain the transient probabilities to determine mean-time-to-failure and reliability function and further steady state availability of the repairable system. As the system parameters are uncontrollable factors; thus the life times, repair times and recovery/reboot time are assumed to be as uncertain or fuzzified distributions.Design/methodology/approachThe fuzzy approach is introduced to investigate the reliability measures of load sharing repairable system which consists of two operating units and one standby unit. On the failure of an operating component, it is instantly spotted, located and sent for recovery procedures with coverage probability. In case of imperfect recovery, reboot takes place.FindingsOn the basis of extension principle and mathematical programming approach, the authors establish membership functions for system characteristics with the help of α-cuts. To demonstrate the practical validity of the proposed fuzzified model, numerical illustrations are performed.Originality/valueThe model proposed for reliability analysis may cheer up the continuance of the work towards more applications in repairable systems. Therefore, the reader is provided with useful intuition into the nature of fuzzy computations and practical amendments while measuring ambiguous data.
{"title":"Load sharing repairable system with imperfect coverage in fuzzy environment","authors":"Ritu Gupta, Zainab Tasneem","doi":"10.1108/ijqrm-08-2021-0298","DOIUrl":"https://doi.org/10.1108/ijqrm-08-2021-0298","url":null,"abstract":"PurposeThe purpose of this study is to develop Markovian model to obtain the transient probabilities to determine mean-time-to-failure and reliability function and further steady state availability of the repairable system. As the system parameters are uncontrollable factors; thus the life times, repair times and recovery/reboot time are assumed to be as uncertain or fuzzified distributions.Design/methodology/approachThe fuzzy approach is introduced to investigate the reliability measures of load sharing repairable system which consists of two operating units and one standby unit. On the failure of an operating component, it is instantly spotted, located and sent for recovery procedures with coverage probability. In case of imperfect recovery, reboot takes place.FindingsOn the basis of extension principle and mathematical programming approach, the authors establish membership functions for system characteristics with the help of α-cuts. To demonstrate the practical validity of the proposed fuzzified model, numerical illustrations are performed.Originality/valueThe model proposed for reliability analysis may cheer up the continuance of the work towards more applications in repairable systems. Therefore, the reader is provided with useful intuition into the nature of fuzzy computations and practical amendments while measuring ambiguous data.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44606056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-03DOI: 10.1108/ijqrm-08-2021-0281
Anwesa Kar, G. Sharma, R. Rai
PurposeIn order to minimize the impact of variability on performance of the process, proper understanding of factors interdependencies and their impact on process variability (PV) is required. However, with insufficient/incomplete numerical data, it is not possible to carry out in-depth process analysis. This paper presents a qualitative framework for analyzing factors causing PV and estimating their influence on overall performance of the process.Design/methodology/approachFuzzy analytic hierarchy process is used to evaluate the weight of each factor and Bayesian network (BN) is utilized to address the uncertainty and conditional dependencies among factors in each step of the process. The weighted values are fed into the BN for evaluating the impact of each factor to the process. A three axiom-based approach is utilized to partially validate the proposed model.FindingsA case study is conducted on fused filament fabrication (FFF) process in order to demonstrate the applicability of the proposed technique. The result analysis indicates that the proposed model can determine the contribution of each factor and identify the critical factor causing variability in the FFF process. It can also helps in estimating the sigma level, one of the crucial performance measures of a process.Research limitations/implicationsThe proposed methodology is aimed to predict the process quality qualitatively due to limited historical quantitative data. Hence, the quality metric is required to be updated with the help of empirical/field data of PV over a period of operational time. Since the proposed method is based on qualitative analysis framework, the subjectivities of judgments in estimating factor weights are involved. Though a fuzzy-based approach has been used in this paper to minimize such subjectivity, however more advanced MCDM techniques can be developed for factor weight evaluation.Practical implicationsAs the proposed methodology uses qualitative data for analysis, it is extremely beneficial while dealing with the issue of scarcity of experimental data.Social implicationsThe prediction of the process quality and understanding of difference between product target and achieved reliability before the product fabrication will help the process designer in correcting/modifying the processes in advance hence preventing substantial amount of losses that may happen due to rework and scraping of the products at a later stage.Originality/valueThis qualitative analysis will deal with the issue of data unavailability across the industry. It will help the process designer in identifying root cause of the PV problem and improving performance of the process.
{"title":"A fuzzy Bayesian network-based approach for modeling and analyzing factors causing process variability","authors":"Anwesa Kar, G. Sharma, R. Rai","doi":"10.1108/ijqrm-08-2021-0281","DOIUrl":"https://doi.org/10.1108/ijqrm-08-2021-0281","url":null,"abstract":"PurposeIn order to minimize the impact of variability on performance of the process, proper understanding of factors interdependencies and their impact on process variability (PV) is required. However, with insufficient/incomplete numerical data, it is not possible to carry out in-depth process analysis. This paper presents a qualitative framework for analyzing factors causing PV and estimating their influence on overall performance of the process.Design/methodology/approachFuzzy analytic hierarchy process is used to evaluate the weight of each factor and Bayesian network (BN) is utilized to address the uncertainty and conditional dependencies among factors in each step of the process. The weighted values are fed into the BN for evaluating the impact of each factor to the process. A three axiom-based approach is utilized to partially validate the proposed model.FindingsA case study is conducted on fused filament fabrication (FFF) process in order to demonstrate the applicability of the proposed technique. The result analysis indicates that the proposed model can determine the contribution of each factor and identify the critical factor causing variability in the FFF process. It can also helps in estimating the sigma level, one of the crucial performance measures of a process.Research limitations/implicationsThe proposed methodology is aimed to predict the process quality qualitatively due to limited historical quantitative data. Hence, the quality metric is required to be updated with the help of empirical/field data of PV over a period of operational time. Since the proposed method is based on qualitative analysis framework, the subjectivities of judgments in estimating factor weights are involved. Though a fuzzy-based approach has been used in this paper to minimize such subjectivity, however more advanced MCDM techniques can be developed for factor weight evaluation.Practical implicationsAs the proposed methodology uses qualitative data for analysis, it is extremely beneficial while dealing with the issue of scarcity of experimental data.Social implicationsThe prediction of the process quality and understanding of difference between product target and achieved reliability before the product fabrication will help the process designer in correcting/modifying the processes in advance hence preventing substantial amount of losses that may happen due to rework and scraping of the products at a later stage.Originality/valueThis qualitative analysis will deal with the issue of data unavailability across the industry. It will help the process designer in identifying root cause of the PV problem and improving performance of the process.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43048099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-03DOI: 10.1108/ijqrm-08-2021-0297
V. Yadav, Pardeep Gahlot
PurposeThe purpose of this study is to integrate Green technology, Lean and Six Sigma methodology under the umbrella of Green Lean Six Sigma (GLSS). Further, the study also proposes an eight facet GLSS framework for small and medium enterprises (SMEs) to enhance organizational sustainability.Design/methodology/approachIn this study, GLSS integration has been proposed based on intangible features like barriers, challenges, toolsets, etc. Moreover, the GLSS framework has been realized based on Six Sigma well-known define, measure, analyze, improve and control (DMAIC) approach.FindingsIt has been found that lack of customer involvement, financial constraints and ignorance towards Kaizen are the most pre-eminent barriers for GLSS execution. Further, it has been found that most frequently used GLSS tools are the 5S, environmental value stream mapping (EVSM) and life cycle assessment (LCA). The proposed GLSS framework encompasses systematic application of different GLSS tools that lead improved organization sustainability.Practical implicationsThe present study will facilitate industrial managers to incorporate the GLSS approach in their business process through systematic understanding of key elements related to this sustainable approach. This study further prompts practitioner to incorporate GLSS in industry through systematic adoption of the proposed framework for improved environmental performance.Social implicationsThis work provides detailed knowledge for the researchers and academicians by dispensing awareness into integral measures and framework. GLSS toolsets dispensed in this work augments academicians and researchers to make decision which tools to be used at distinct phases of GLSS project execution.Originality/valueThe present study is the first of its kind that provides integral measures and GLSS framework for SMEs.
{"title":"Green Lean Six Sigma sustainability-oriented framework for small and medium enterprises","authors":"V. Yadav, Pardeep Gahlot","doi":"10.1108/ijqrm-08-2021-0297","DOIUrl":"https://doi.org/10.1108/ijqrm-08-2021-0297","url":null,"abstract":"PurposeThe purpose of this study is to integrate Green technology, Lean and Six Sigma methodology under the umbrella of Green Lean Six Sigma (GLSS). Further, the study also proposes an eight facet GLSS framework for small and medium enterprises (SMEs) to enhance organizational sustainability.Design/methodology/approachIn this study, GLSS integration has been proposed based on intangible features like barriers, challenges, toolsets, etc. Moreover, the GLSS framework has been realized based on Six Sigma well-known define, measure, analyze, improve and control (DMAIC) approach.FindingsIt has been found that lack of customer involvement, financial constraints and ignorance towards Kaizen are the most pre-eminent barriers for GLSS execution. Further, it has been found that most frequently used GLSS tools are the 5S, environmental value stream mapping (EVSM) and life cycle assessment (LCA). The proposed GLSS framework encompasses systematic application of different GLSS tools that lead improved organization sustainability.Practical implicationsThe present study will facilitate industrial managers to incorporate the GLSS approach in their business process through systematic understanding of key elements related to this sustainable approach. This study further prompts practitioner to incorporate GLSS in industry through systematic adoption of the proposed framework for improved environmental performance.Social implicationsThis work provides detailed knowledge for the researchers and academicians by dispensing awareness into integral measures and framework. GLSS toolsets dispensed in this work augments academicians and researchers to make decision which tools to be used at distinct phases of GLSS project execution.Originality/valueThe present study is the first of its kind that provides integral measures and GLSS framework for SMEs.","PeriodicalId":14193,"journal":{"name":"International Journal of Quality & Reliability Management","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45525944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-02DOI: 10.1108/ijqrm-10-2021-0364
Mohit Goswami, Y. Daultani
PurposeThis study aims to devise generalized unconstrained optimization models for ascertaining the optimal level of product quality and production capacity level by modeling both product price and production cost as a function of product quality. Further, interrelations among investment for quality, product quality and production volume are considered. This study contributes toward the extant research, in that nuances related to price, production volume, and product quality are fused together such that two broad operational strategies of product quality optimization and production capacity optimization can be contrasted.Design/methodology/approachTo achieve the research objectives, the authors evolve unconstrained optimization models such that optimal product quality level and optimal production capacity level can be obtained employing the principles of differential calculus aimed at maximizing the manufacturer's profit. Specifically, nuances related to quality technology and efficiency, and quality loss cost has also been integrated in the integrated model. Thereafter, employing numerical analysis for a generalized product, the detailed workings of evolved models are demonstrated. The authors further carry out the sensitivity analysis to understand the impact of investment for quality onto the manufacturer's profit for both operational strategies.FindingsThe research demonstrates that the manufacturer would be better off adopting production capacity optimization strategy as an operational policy, as opposed to product quality optimization policy for the manufacturer's profit maximization. Further, considering the two operational strategies, the manufacturer does not obtain the highest possible theoretical profit when pertinent variables (product quality and production capacity) are set at highest possible theoretical level. This research discusses that in low-volume and high-margin products, it might be useful to adopt a product quality optimization strategy as a production capacity optimization strategy results in significantly high quality loss cost.Originality/valueThe findings of our study have a significant implication for industries such as steel-making, cement production, automotive industry wherein the conventional wisdom dictates that higher level of production capacity utilization always results in higher level of revenues. However, the authors deduce that beyond certain production capacity utilization, striving for higher utilization does not fetch additional profit. This work also adds to the extant research literature, in that it integrates the nuances of product quality, production volume and pricing in an integrative manner.
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