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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.

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.

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.

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.

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.

Drawing upon the stimulus-organism-response model, this study aims to explore the impact of soft aspects of service quality on revisit intention through the mechanism of perceived empathy.

For the examination of the hypothesized relationships, the study adopts structural equation modelling to analyse the data of 562 respondents (i.e. 281 family members and 281 inpatients).

The empirical results suggest that service quality increased family member empathy perception, which, in turn, improved inpatients’ revisit intentions.

Past studies have focused on the roles of overall service quality. The authors have extended the literature by examining the specific but important aspect of service quality and its effects on emotional response. Importantly, the study explains that the affective reactions of a patient’s family, fastened with perceived empathy, have a central role in influencing the patients’ subsequent reactions. Moreover, the prior studies collected the data either from hospital employees or patients. However, in the present study, the authors used a unique sample (family members as well as patients) to have a deeper understanding. Thus, the study enhances the literature on the stimuli-response (i.e. service quality – revisit intentions) relationship in the context of service marketing in general and health care in specific. Important academic and managerial contributions and recommendations for future research are discussed.

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

The authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.

The study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).

This research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

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.

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

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.

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.

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.

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.

This review paper aims to explore and investigate the Quality 4.0 current knowledge, emerging areas, and trends available in the literature and provide insights for future research directions. The bibliometric analysis determines the most prominent journals, authors, countries, articles, and themes. The Citation and PageRank analysis identifies the most influential and prestigious articles. The author's keyword analysis identifies the research theme, patterns, and trends within a particular area of research.

This study utilised the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) declaration as a review protocol, and the data is retrieved accordingly. Therefore, 104 articles from Scopus and 28 from Web of Science were combined in R-Environment, and 25 duplicates were removed using RStudio. Finally, 107 papers were selected for further analysis. After the abstract level screening, the study reviewed 99 articles bibliographically published in peer-reviewed journals from prominent academic databases Scopus and WoS between 2011 to April 2023. We used the VOSviewer software tool for analysing bibliometric networks that allow the construction, visualisation, and exploration of maps based on any form of network data.

The review identified emerging themes: artificial intelligence, digitalization, sustainability, root cause analysis, topic modelling, and digital voice-of-customers. To establish the intellectual structure of the field and identify gaps, co-citation and content analysis were used. The content of 49 papers in the identified clusters was then carefully analysed. The four primary themes are the relationship of Quality 4.0 with Industry 4.0, the conceptualization of Quality 4.0, recommendations for the new Quality 4.0 model, and the impact of Quality 4.0. The findings provide an excellent foundation for future research in this field for policymakers, managers, practitioners, and academia.

This is the first systematic literature review-cum-bibliometric analysis on quality 4.0 that covers the field comprehensively. Based on the present review, the paper proposes six possible future research directions to investigate.

Facilities management (FM) as a strategic management tool has been an attractive research topic among scholars and practitioners alike for decades. The primary purpose of this paper is threefold: to assess the extent of use of FM roles (strategic, tactical and operational); to examine user satisfaction of service quality performance; and to analyse the influence of FM roles on service quality performance using data from Nigeria’s banking sector.

Relying on exploratory cross-sectional survey, 350 copies of a structured questionnaire were purposively distributed to senior management staff, bank staff, FM supervisors and bank customers in Lagos, Nigeria. One hundred and forty valid responses were returned to give a response rate of 40%. Data collected were analysed using descriptive, Spearman rank correlation and Kruskal–Wallis tests.

It was discovered that strategic facilities planning, IT planning strategy and real estate decisions are the most important FM roles at the strategic level; resource management, data control and planning change at the tactical level; and implementations, building operations and emergencies at the operation level. Findings equally revealed that visual appealing of materials associated with services (tangibles), insisting on error-free records (reliability), willing to help (responsiveness), having the knowledge to answer questions (assurance) and giving individualised attention (empathy) were the most important service quality performance indicators. Furthermore, the study revealed that strategic FM roles significantly influenced tangibles, reliability and responsiveness of staff and the services. Besides, tactical FM roles significantly influenced all service quality indicators except assurance, while operational FM roles had significant influence on tangibles, responsiveness and empathy.

To the best of the author’s knowledge, this study has provided first ever insight into the extent of FM strategic roles in the banking sector and influence of FM roles on service quality performance.

The industrial revolution changed the market landscape significantly in all industrial sectors. It has a noteworthy impact on enhancing the quality of goods and services. The quality aspect is of utmost concern and determines the success or failure of any product. Therefore, the presented study analyses the key barriers and solutions of Quality 4.0.

Twenty barriers and fifteen solutions were identified using a literature review and investigated using a hybrid approach. Barrier weights were evaluated with the help of the fuzzy AHP method. Furthermore, the computed weights were used to perform computations in the next step using fuzzy-TOPSIS to prioritize the ranking of identified solutions.

The research results show that “Lack of applying advanced analytics to uncover Quality 4.0 initiatives” and “Lack of integrating data from various sources across the organization” are the topmost barriers. Furthermore, “Implement a leadership development program focused on Quality 4.0” and “Cross-departmental peer learning environment” are the topmost solutions.

Managers and industrialists can benefit from Quality 4.0 through improved decision-making, process efficiency, supply chain collaboration, agile quality management, enhanced customer experience and a culture of continuous improvement. This results in better quality, operational effectiveness and a competitive edge.

The solutions need to be mapped with barriers to adopting Quality 4.0. Furthermore, the research results involve novelty by prioritizing the solutions to overcome the anticipated barriers.

Quality has always been a competitive advantage for every organisation that strives for customer satisfaction when offering services or products. Technological advancements during the industrial revolutions have enabled organisations to grub improvement and transition opportunities into a new paradigm in operating business processes. In light of the fourth industrial revolution (FIR), in which Quality 4.0 (Q4.0) leveraged its technologies, this study establishes the need for service organisations to transition to Q4.0. It unveils the awareness level within the organisation, the existing challenges and the benefits of transitioning to Q4.0.

The data for this study was acquired through a survey methodology; it involved qualitative and quantitative methodologies and a mix of primary and secondary sources. The challenges and benefits regarding Q4.0 adoption were obtained from the relevant literature and used as a base of assessment in the selected service organisations. Minitab version 20 and SPSS 21.0 software packages analysed the gathered data.

The study found a high level of awareness regarding Q4.0 among the selected service organisations. Despite the high level of awareness, it was revealed that neither of the Q4.0-related technologies have been implemented nor in the process within the selected service industries. This is due to numerous challenges, including inadequate high-speed internet, a high cost of investment, inadequate skilled personnel and inadequate scepticalness to the implementation outcomes. Despite these challenges, leveraged technologies, potential benefits and Q4.0 awareness all demonstrate the need for Q4.0.

The study introduces the advent of the FIR and the disruptive nature of the associated technologies. It also unveils the potential of the contemporary technologies of the FIR that could elevate quality service provision to increase their competitiveness. Moreover, it also assists service organisations in planning and properly allocating their resources to ensure all the challenges are addressed in the Q4.0 adoption process. The study is limited in that it merely considers service organisations in Tanzania without categorising what type of service organisations were considered, i.e. banking, telecommunications, health, etc. thus generalising the findings.

Much has been discussed in the literature regarding Q4.0 in manufacturing organisations, focusing less on service organisations. This study uniquely assessed the need to transition to Q4.0 for service organisations, which has yet to be covered in the literature.

This study proposes a machine learning framework to predict customer complaints from production line tests in an automotive company's lot-release process, enhancing Quality 4.0. It aims to design and implement the framework, compare different machine learning (ML) models and evaluate a non-sampling threshold-moving approach for adjusting prediction capabilities based on product requirements.

This study applies the Cross-Industry Standard Process for Data Mining (CRISP-DM) and four ML models to predict customer complaints from automotive production tests. It employs cost-sensitive and threshold-moving techniques to address data imbalance, with the F1-Score and Matthews correlation coefficient assessing model performance.

The framework effectively predicts customer complaint-related tests. XGBoost outperformed the other models with an F1-Score of 72.4% and a Matthews correlation coefficient of 75%. It improves the lot-release process and cost efficiency over heuristic methods.

The framework has been tested on real-world data and shows promising results in improving lot-release decisions and reducing complaints and costs. It enables companies to adjust predictive models by changing only the threshold, eliminating the need for retraining.

To the best of our knowledge, there is limited literature on using ML to predict customer complaints for the lot-release process in an automotive company. Our proposed framework integrates ML with a non-sampling approach, demonstrating its effectiveness in predicting complaints and reducing costs, fostering Quality 4.0.

The aim of this paper is to explore and analyse the challenges in effective implementation of blockchain by human resource management (HRM) functions. This paper also aims to assess the interplay between the barriers in causing the challenges during blockchain execution.

Ten barriers are discovered from the past studies. Based on the expert views on the identified barriers interpretive structural modelling (ISM) is administered to understand the interplay of these 10 challenges resulting in ineffective or non-implementation of HR blockchain.

The application of ISM has helped in categorizing the variables into strategic, operational and performance outcomes. Results of ISM indicate key barriers like lack of expertise, data privacy, technical infeasibility, complexity in implantation and lack of used cases.

The research is limited to 10 barriers. There can be other barriers that can also be studied. Second, the research is proposing a conceptual model that needs further validation.

This paper has significant implications for the theoretical and practical body of knowledge. So far, most studies are exploring and describing HRM from a digital perspective. Most HR studies are on artificial intelligence, the Internet of Things and smart HRM. Previous studies on blockchain for HRM are mostly describing the advantages of going for it.

Based on the findings, it can also be suggested that policy formulators must advance the technical regulatory framework. Blockchain technology can be effectively implemented only if the top management is committed to it because they can only frame the rules and right control framework, affirm the governance process and strategize improvement.

The study offers insights into the organization's decision makers for effectively implementing blockchain into their HR systems. Some specific recommendations based on the results are also made. The paper is an innovative attempt to analyse the barriers to HR blockchain.