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Article
Publication date: 1 January 2024

Diana Oliveira, Helena Alvelos and Maria J. Rosa

Quality 4.0 is being presented as the new stage of quality development. However, its overlying concept and rationale are still hard to define. To better understand what different…

Abstract

Purpose

Quality 4.0 is being presented as the new stage of quality development. However, its overlying concept and rationale are still hard to define. To better understand what different authors and studies advocate being Quality 4.0, a systematic literature review was undertaken on the topic. This paper presents the results of such review, providing some avenues for further research on quality management.

Design/methodology/approach

The documents for the systematic literature review have been searched on the Scopus database, using the search equation: [TITLE-ABS-KEY (“Quality 4.0”) OR TITLE-ABS-KEY (Quality Management” AND (“Industry 4.0” OR “Fourth Industr*” OR i4.0))]. Documents were filtered by language and by type. Of the 367 documents identified, 146 were submitted to exploratory content analysis.

Findings

The analyzed documents essentially provide theoretical discussions on what Quality 4.0 is or should be. Five categories have emerged from the content analysis undertaken: Industry 4.0 and the Rise of a New Approach to Quality; Motivations, Readiness Factors and Barriers to a Quality 4.0 Approach; Digital Quality Management Systems; Combination of Quality Tools and Lean Methodologies and Quality 4.0 Professionals.

Research limitations/implications

It was hard to find studies reporting how quality is actually being managed in organizations that already operate in the Industry 4.0 paradigm. Answers could not be found to questions regarding actual practices, methodologies and tools being used in Quality 4.0 approaches. However, the research undertaken allowed to identify in the literature different ways of conceptualizing and analyzing Quality 4.0, opening up avenues for further research on quality management in the Industry 4.0 era.

Originality/value

This paper offers a broad look at how quality management is changing in response to the affirmation of the Industry 4.0 paradigm.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 23 January 2024

Ranjit Roy Ghatak and Jose Arturo Garza-Reyes

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by…

Abstract

Purpose

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by incorporating Industry 4.0 technological innovations into existing quality management frameworks, signifying a significant evolution in quality control systems. Despite the evident advantages, the practical deployment in the Indian manufacturing sector encounters various obstacles. This research is dedicated to a thorough examination of these impediments. It is structured around a set of pivotal research questions: First, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Second, it aims to elucidate these barriers' interrelations and mutual dependencies. Thirdly, the research prioritizes these barriers in terms of their significance to the adoption process. Finally, it contemplates the ramifications of these priorities for the strategic advancement of manufacturing practices and the development of informed policies. By answering these questions, the research provides a detailed understanding of the challenges faced. It offers actionable insights for practitioners and policymakers implementing Quality 4.0 in the Indian manufacturing sector.

Design/methodology/approach

Employing Interpretive Structural Modelling and Matrix Impact of Cross Multiplication Applied to Classification, the authors probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorized according to their driving power and dependence, providing a richer understanding of the dynamic obstacles within the Technology–Organization–Environment (TOE) framework.

Findings

The study results highlight the lack of Quality 4.0 standards and Big Data Analytics (BDA) tools as fundamental obstacles to integrating Quality 4.0 within the Indian manufacturing sector. Additionally, the study results contravene dominant academic narratives, suggesting that the cumulative impact of organizational barriers is marginal, contrary to theoretical postulations emphasizing their central significance in Quality 4.0 assimilation.

Practical implications

This research provides concrete strategies, such as developing a collaborative platform for sharing best practices in Quality 4.0 standards, which fosters a synergistic relationship between organizations and policymakers, for instance, by creating a joint task force, comprised of industry leaders and regulatory bodies, dedicated to formulating and disseminating comprehensive guidelines for Quality 4.0 adoption. This initiative could lead to establishing industry-wide standards, benefiting from the pooled expertise of diverse stakeholders. Additionally, the study underscores the necessity for robust, standardized Big Data Analytics tools specifically designed to meet the Quality 4.0 criteria, which can be developed through public-private partnerships. These tools would facilitate the seamless integration of Quality 4.0 processes, demonstrating a direct route for overcoming the barriers of inadequate standards.

Originality/value

This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE framework, detailing how these barriers interact with and influence each other, particularly highlighting the previously overlooked environmental factors. The analysis reveals a critical interdependence between “lack of standards for Quality 4.0” and “lack of standardized BDA tools and solutions,” providing nuanced insights into their conjoined effect on stalling progress in this field. Moreover, the study contributes to the theoretical body of knowledge by mapping out these novel impediments, offering a more comprehensive understanding of the challenges faced in adopting Quality 4.0.

Details

International Journal of Quality & Reliability Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 23 March 2023

Haftu Hailu Berhe, Hailekiros Sibhato Gebremichael and Kinfe Tsegay Beyene

Existing conceptual, empirical and case studies evidence suggests that manufacturing industries find the joint implementation of Kaizen philosophy initiatives. However, the…

Abstract

Purpose

Existing conceptual, empirical and case studies evidence suggests that manufacturing industries find the joint implementation of Kaizen philosophy initiatives. However, the existing practices rarely demonstrated in a single framework and implementation procedure in a structure nature. This paper, therefore, aims to develop, validate and practically test a framework and implementation procedure for the implementation of integrated Kaizen in manufacturing industries to attain long-term improvement of operational, innovation, business (financial and marketing) processes, performance and competitiveness.

Design/methodology/approach

The study primarily described the problem, extensively reviewed the current state-of-the-art literature and then identified a gap. Based on it, generic and comprehensive integrated framework and implementation procedure is developed. Besides, the study used managers, consultants and academics from various fields to validate a framework and implementation procedure for addressing business concerns. In this case, the primary data was collected through self-administered questionnaire, and 244 valid questionnaires were received and were analyzed. Furthermore, the research verified the practicability of the framework by empirically exploring the current scenario of selected manufacturing companies.

Findings

The research discovered innovative framework and six-phase implementation procedure to fill the existing conceptual gap. Furthermore, the survey-based and exploratory empirical analysis of the research demonstrated that the practice of the proposed framework based on structured procedure is valued and companies attain the middling improvements of productivity, delivery time, quality, 5S practice, waste and accident rate by 61.03, 44, 52.53, 95.19, 80.12, and 70.55% respectively. Additionally, the companies saved a total of 14933446 ETH Birr and 5,658 M2 free spaces. Even though, the practices and improvements vary from company to company, and even companies unable to practice some of the unique techniques of the identified CI initiatives considered in the proposed framework.

Research limitations/implications

All data collected in the survey came from professionals working for Ethiopian manufacturing companies, universities and government. It is important to highlight that n = 244 is high sample size, which is adequate for a preliminary survey but reinforcing still needs further survey in terms of generalization of the results since there are hundreds of manufacturing companies, consultants and academicians implementing and consulting Kaizen. Therefore, a further study on a wider Ethiopian manufacturing companies, consultants and academic scale would be informative.

Practical implications

This work is very important for Kaizen professionals in the manufacturing industry, academic and government but in particular for senior management and leadership teams. Aside from the main findings on framework development, there is some strong evidence that practice of Kaizen resulted in achieving quantitative (monetary and non-monetary) and qualitative results. Thus, senior management teams should use this research out to practice and analyze the effect of Kaizen on their own organizations. Within the academic community, this study is one of the first focusing on development, validating and practically testing and should aid further study, research and understanding of Kaizen in manufacturing industries.

Originality/value

So far, it is rare to find preceding studies proposed, validated and practically test an integrated Kaizen framework with the context of manufacturing industries. Thus, authors understand that this is the very first research focused on the development of the framework for manufacturing industries continuously to be competitive and could help managers, institutions, practitioners and academicians in Kaizen practice.

Details

International Journal of Quality & Reliability Management, vol. 40 no. 10
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 4 March 2024

Janet Chang, Klaudia Jaskula, Eleni Papadonikolaki, Dimitrios Rovas and Ajith Kumar Parlikad

This research investigates the distinct characteristics of blockchain technology to safeguard against the deterioration of handover information quality in the post-construction…

Abstract

Purpose

This research investigates the distinct characteristics of blockchain technology to safeguard against the deterioration of handover information quality in the post-construction phase. The significance of effective management of handover information is highlighted by global building failures, such as the Grenfell Tower fire in London, UK. Despite existing technological interventions, there remains a paucity of understanding regarding the factors contributing to the decline in the quality of handover information during the post-construction phase.

Design/methodology/approach

This study employed a multi-case studies approach across five higher education institutions. It involved conducting semi-structured interviews with 52 asset management professionals, uncovering the underlying reasons for the decline in handover information quality. Building on these insights, the study performed a mapping exercise to align these identified factors with blockchain technology features and information quality dimensions, aiming to evaluate blockchain’s potential in managing quality handover information.

Findings

The study findings suggest that blockchain technology offers advantages but has limitations in addressing all the identified quality issues of managing handover information. Due to the lack of an automated process and file-based information exchange, updating handover information still requires an error-prone manual process, leading to potential information loss. Additionally, no solutions are available for encoding drawings for updates and validation.

Originality/value

This study proposes a framework integrating blockchain to enhance the information management process and improve handover information quality.

Details

Built Environment Project and Asset Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-124X

Keywords

Book part
Publication date: 28 September 2023

Emil Velinov, Marta Kadłubek, Eleftherios Thalassinos, Simon Grima and Dimitrios Maditinos

The chapter sheds light on how top management teams (TMTs) across multinational firms tackle the ongoing disruptive digital transformation during the pandemic era. The chapter…

Abstract

The chapter sheds light on how top management teams (TMTs) across multinational firms tackle the ongoing disruptive digital transformation during the pandemic era. The chapter includes basic definitions and global and regional trends on data governance and digital transformation across multinational firms from advanced and emerging markets. Finally, it provides several case studies demonstrating the theoretical and practical applicability of how data governance and digital transformation emerged from top management team perspectives. The chapter outlines the importance of leadership and top management in dealing with emerging technologies and business processes across global firms.

Details

Digital Transformation, Strategic Resilience, Cyber Security and Risk Management
Type: Book
ISBN: 978-1-80455-254-4

Keywords

Open Access
Article
Publication date: 12 October 2023

Jiju Antony, Arshia Kaul, Shreeranga Bhat, Michael Sony, Vasundhara Kaul, Maryam Zulfiqar and Olivia McDermott

This study aims to investigate the adoption of Quality 4.0 (Q4.0) and assess the critical failure factors (CFFs) for its implementation and how its failure is measured.

Abstract

Purpose

This study aims to investigate the adoption of Quality 4.0 (Q4.0) and assess the critical failure factors (CFFs) for its implementation and how its failure is measured.

Design/methodology/approach

A qualitative study based on in-depth interviews with quality managers and executives was conducted to establish the CFFs for Q4.0.

Findings

The significant CFFs highlighted were resistance to change and a lack of understanding of the concept of Q4.0. There was also a complete lack of access to or availability of training around Q4.0.

Research limitations/implications

The study enhances the body of literature on Q4.0 and is one of the first research studies to provide insight into the CFFs of Q4.0.

Practical implications

Based on the discussions with experts in the area of quality in various large and small organizations, one can understand the types of Q4.0 initiatives and the CFFs of Q4.0. By identifying the CFFs, one can establish the steps for improvements for organizations worldwide if they want to implement Q4.0 in the future on the competitive global stage.

Originality/value

The concept of Q4.0 is at the very nascent stage, and thus, the CFFs have not been found in the extant literature. As a result, the article aids businesses in understanding possible problems that might derail their Q4.0 activities.

Details

International Journal of Quality & Reliability Management, vol. 41 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 3 November 2022

Reza Edris Abadi, Mohammad Javad Ershadi and Seyed Taghi Akhavan Niaki

The overall goal of the data mining process is to extract information from an extensive data set and make it understandable for further use. When working with large volumes of…

Abstract

Purpose

The overall goal of the data mining process is to extract information from an extensive data set and make it understandable for further use. When working with large volumes of unstructured data in research information systems, it is necessary to divide the information into logical groupings after examining their quality before attempting to analyze it. On the other hand, data quality results are valuable resources for defining quality excellence programs of any information system. Hence, the purpose of this study is to discover and extract knowledge to evaluate and improve data quality in research information systems.

Design/methodology/approach

Clustering in data analysis and exploiting the outputs allows practitioners to gain an in-depth and extensive look at their information to form some logical structures based on what they have found. In this study, data extracted from an information system are used in the first stage. Then, the data quality results are classified into an organized structure based on data quality dimension standards. Next, clustering algorithms (K-Means), density-based clustering (density-based spatial clustering of applications with noise [DBSCAN]) and hierarchical clustering (balanced iterative reducing and clustering using hierarchies [BIRCH]) are applied to compare and find the most appropriate clustering algorithms in the research information system.

Findings

This paper showed that quality control results of an information system could be categorized through well-known data quality dimensions, including precision, accuracy, completeness, consistency, reputation and timeliness. Furthermore, among different well-known clustering approaches, the BIRCH algorithm of hierarchical clustering methods performs better in data clustering and gives the highest silhouette coefficient value. Next in line is the DBSCAN method, which performs better than the K-Means method.

Research limitations/implications

In the data quality assessment process, the discrepancies identified and the lack of proper classification for inconsistent data have led to unstructured reports, making the statistical analysis of qualitative metadata problems difficult and thus impossible to root out the observed errors. Therefore, in this study, the evaluation results of data quality have been categorized into various data quality dimensions, based on which multiple analyses have been performed in the form of data mining methods.

Originality/value

Although several pieces of research have been conducted to assess data quality results of research information systems, knowledge extraction from obtained data quality scores is a crucial work that has rarely been studied in the literature. Besides, clustering in data quality analysis and exploiting the outputs allows practitioners to gain an in-depth and extensive look at their information to form some logical structures based on what they have found.

Details

Information Discovery and Delivery, vol. 51 no. 4
Type: Research Article
ISSN: 2398-6247

Keywords

Article
Publication date: 1 December 2022

Ankesh Mittal, Vimal Kumar, Pratima Verma and Arpit Singh

The study aims to identify organizational variables of quality 4.0 for an Indian manufacturing company in the case of digital transformation. Furthermore, the organization…

Abstract

Purpose

The study aims to identify organizational variables of quality 4.0 for an Indian manufacturing company in the case of digital transformation. Furthermore, the organization enhances its quality 4.0 performances to its success based on the degree of relevance of these variables, insight into these variables and sub-factors to prioritize them.

Design/methodology/approach

Initially, two rounds of the survey were conducted with 11 decision-makers from the company made to receive organizational variables scores and prioritize the factors and sub-factors. Analytic Hierarchy Process (AHP) based research methodology has been proposed to assign the criterion weights and prioritize the identified variables.

Findings

The results of this AHP model demonstrate that “Committed Leadership” is recognized as the top positioned variable and most significant organizational variable, followed by Collaboration and Quality culture, which are developed at the next level. These essential organizational variables with their sub-categories' priorities are identified as contributing attributes.

Research limitations/implications

The findings facilitate quality 4.0 in the digitalization era, which take into contemplating the current state of the business. Furthermore, the understanding of variables provides insightful guidance to analyze, solve complex problems and assess the efficacy of quality 4.0 in digital transformation.

Originality/value

The novelty of this study is to pinpoint, and evaluate the responsible organizational variables and prioritize them that lead to high productivity and competitive advantage considering the AHP method.

Details

The TQM Journal, vol. 36 no. 1
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 23 October 2023

Abhijeet Tewary and Vaishali Jadon

This research aims to analyze the literature on Quality 4.0 and pinpoint the essential factors contributing to its success. Additionally, the research aims to develop a framework…

Abstract

Purpose

This research aims to analyze the literature on Quality 4.0 and pinpoint the essential factors contributing to its success. Additionally, the research aims to develop a framework that can be used to create a capable workforce necessary for the successful implementation of Quality 4.0.

Design/methodology/approach

By following a systematic approach, the authors could ensure that their literature review was comprehensive and unbiased. Using a set of pre-determined inclusion and exclusion criteria, the authors screened 90 research articles to obtain the most relevant and reliable information for their study.

Findings

The authors' review identified essential findings, including the evolution of literature in the field of Quality 4.0 and the systematization of previous literature reviews focusing on training and development. The authors also identified several training barriers to implementing Quality 4.0 and proposed a model for building a competent workforce using Kolb's experiential learning model.

Practical implications

The authors' research offers insights into the training barriers that must be considered when building a competent workforce. Using the framework proposed in the authors' research, consultants and managers can better integrate Quality 4.0 into their organizations.

Social implications

The adoption of Quality 4.0 has significant social implications and is essential for advancing sustainability. It can improve efficiency, reduce waste, minimize environmental impacts and better meet the needs and expectations of stakeholders.

Originality/value

The authors' study stands out as one of the earliest reviews of the literature on Quality 4.0 to incorporate the theory-context-method (TCM) framework, allowing to provide unique insights into future research directions that had not been previously explored.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 3 April 2023

Efrosini Siougle, Sophia Dimelis and Nikolaos Malevris

This study explores the link between ISO 9001 certification, personal data protection and firm performance using financial balance sheet and survey data. The security aspect of…

Abstract

Purpose

This study explores the link between ISO 9001 certification, personal data protection and firm performance using financial balance sheet and survey data. The security aspect of data protection is analyzed based on the major requirements of the General Data Protection Regulation and mapped to the relevant controls of the ISO/IEC 27001/27002 standards.

Design/methodology/approach

The research analysis is based on 96 ISO 9001–certified and non-certified publicly traded manufacturing and service firms that responded to a structured questionnaire. The authors develop and empirically test their theoretical model using the structural equation modeling technique and follow a difference-in-differences econometric modeling approach to estimate financial performance differences between certified and non-certified firms accounting for the level of data protection.

Findings

The estimates indicate three core dimensions in the areas of “policies, procedures and responsibilities,” “access control management” and “risk-reduction techniques” as desirable components in establishing the concept of data security. The estimates also suggest that the data protection level has significantly impacted the performance of certified firms relative to the non-certified. Controlling for the effect of industry-level factors reveals a positive relationship between data security and high-technological intensity.

Practical implications

The results imply that improving the level of compliance to data protection enhances the link between certification and firm performance.

Originality/value

This study fills a gap in the literature by empirically testing the influence of data protection on the relationship between quality certification and firm performance.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 3
Type: Research Article
ISSN: 1741-0401

Keywords

1 – 10 of over 13000