Interpretive model of enablers of Data-Driven Sustainable Quality Management practice in manufacturing industries: ISM approach

IF 3.6 4区管理学 Q2 MANAGEMENT Total Quality Management & Business Excellence Pub Date : 2022-11-11 DOI:10.1080/14783363.2022.2132141

Mahipal Singh, R. Rathi, J. Antony

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引用次数: 2

Abstract

The fourth industrial revolution and updated government regulations on NET zero have enforced manufacturing organizations to adopt sustainable practices in their system. Also, manufacturing units need to deal with huge data sets to sustain the quality of products. In this regard, Data-Driven Sustainability Quality Management (DDSQM) is an interdisciplinary approach that provides an understanding of big data management with due quality and sustainability in manufacturing settings. Regardless of its potential benefits, manufacturing firms in developing economies remain reluctant to follow DDSQM practices. To persuade organizations for adopting DDSQM practices in real-time needs to explore the enablers with their contextual relationship for its successful initiation. In the present study, DDSQM enablers are identified and screened through literature and expert opinions from manufacturing industries. Thereafter, screened enablers are modeled through Interpretive Structural Modeling (ISM) and clustered via MICMAC analysis. The proposed methodology was executed with experts from academics and industries in developing economies. This study constitutes the first strive to explore the contextual relationship among enablers of DDSQM practices in developing countries’ manufacturing industries. The findings can help policymakers of emerging economies to adopt data analytics, quality management, and sustainable practices, that in turn, facilitate the implementation of DDSQM practices.

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制造业数据驱动的可持续质量管理实践的推动者的解释模型:ISM方法

第四次工业革命和更新的政府法规已经迫使制造组织在他们的系统中采用可持续的实践。此外，制造单位需要处理庞大的数据集，以维持产品质量。在这方面，数据驱动的可持续发展质量管理(DDSQM)是一种跨学科的方法，它提供了对大数据管理的理解，在制造环境中具有适当的质量和可持续性。尽管有潜在的好处，发展中经济体的制造企业仍然不愿意遵循DDSQM的做法。为了说服组织实时采用DDSQM实践，需要探索其成功启动的上下文关系的推动者。在本研究中，通过文献和来自制造业的专家意见来识别和筛选DDSQM的促成因素。然后，通过解释结构建模(ISM)对筛选的使能因素进行建模，并通过MICMAC分析进行聚类。拟议的方法是由来自发展中经济体学术界和工业界的专家执行的。本研究首次尝试探索发展中国家制造业中DDSQM实践的推动因素之间的语境关系。研究结果可以帮助新兴经济体的决策者采用数据分析、质量管理和可持续实践，从而促进DDSQM实践的实施。

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来源期刊

Total Quality Management & Business Excellence MANAGEMENT-

CiteScore

8.90

自引率

12.80%

发文量

期刊介绍： Total Quality Management & Business Excellence is an international journal which sets out to stimulate thought and research in all aspects of total quality management and to provide a natural forum for discussion and dissemination of research results. The journal is designed to encourage interest in all matters relating to total quality management and is intended to appeal to both the academic and professional community working in this area. Total Quality Management & Business Excellence is the culture of an organization committed to customer satisfaction through continuous improvement. This culture varies both from one country to another and between different industries, but has certain essential principles which can be implemented to secure greater market share, increased profits and reduced costs. The journal provides up-to-date research, consultancy work and case studies right across the whole field including quality culture, quality strategy, quality systems, tools and techniques of total quality management and the implementation in both the manufacturing and service sectors. No topics relating to total quality management are excluded from consideration in order to develop business excellence.