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Focusing on the adoption of Total Quality Management (TQM) principles in universities, this research paper explores how the “soft” dimensions of TQM trigger its “hard” dimensions considering them at the individual (micro-) and the university (meso-), and eventually at cluster (system-), levels.

Adopting a qualitative approach, this study presents an in-depth, longitudinal case study of University of Siena, one of the oldest Italian universities, that has been at the core of the research-based cluster on vaccines, today converged in the Tuscan Life Science Cluster. In particular, data were collected between 2018 and February 2022 and consists of archival data (press articles, websites, books), nine interviews to key informants, multiyear experience of the Life Sciences sector by two of the authors and other material put at disposal by university offices, and emails. Data analysis relied on a timeline, a coding procedure that considered three levels of analysis (individual, organization and cluster). Finally, the authors looked at the “how” and “why” the emerged themes have contributed to academic excellence.

This paper unveils how “soft” and “hard” sides of TQM are blended across multiple levels for reaching academic excellence. The grounded model emerged enlightens the importance of an individual “soft” dimension, academic passion (composed by its three subdimensions of individual research, teaching and entrepreneurial passion) and also sheds light on the organizational “soft” and “hard” sides that the university has been able to design for encouraging research, teaching and third mission quality. Academic excellence has been possible thanks to the capitalization of the individual and organizational “soft” sides into real outcomes as represented by the organizational and individual “hard” sides.

The paper suggests the importance of TQM principles applied at universities' level, providing an in-depth description of “soft” and “hard” sides dimensions of TQM and their impact on all the three pillars of academic excellence. The study findings suggest implications for managers and professionals in the higher education domain as well as for policymakers emphasizing the importance of supporting the individual and organizational soft sides of TQM. The authors provide practical implications recommending universities to consider not only the organizational dimensions but also individual ones when pursuing higher education excellence. In particular, individual passion plays a crucial role and universities need to identify ways of nurturing it. The authors also recommend policymakers to think about new ways to sustain universities as crucial actors in boosting a cluster development, as well as to consider higher education institutions, especially in more rural areas, as a privileged player not only capable of nurturing academic excellence but also able of creating an internationally renowned cluster.

TQM principles have been intensively analysed from an industrial perspective focusing on manufacturing and services, while this paper focuses on TQM in universities, presenting a grounded model that blends the individual and organizational “soft” and “hard” sides.

The present study conceptualizes total quality management (TQM) in terms of soft and hard aspects and examines their effects on quality performance and patient satisfaction. The indirect effects of soft and hard TQM on patient satisfaction through quality performance are also investigated.

A multi-item questionnaire was prepared to gather primary data from a sample of 312 medical employees in private hospitals in Jordan. The measurement model was evaluated for validity and reliability and determined to be acceptable. Structural equation modeling (SEM) was applied to test the research hypotheses.

The results revealed that soft TQM has a strong positive effect on quality performance and patient satisfaction. Hard TQM was found to positively affect quality performance but to a lesser extent compared to soft TQM. The effect of hard TQM on patient satisfaction, meanwhile, was not significant. Quality performance positively mediated the relationship between TQM – both soft and hard – and patient satisfaction.

This study is one of the first to conceptualize TQM in terms of soft and hard aspects in a health care context. It offers valuable insights for managers of private hospitals looking to enhance quality performance and patient satisfaction. The results reveal that soft TQM is the primary driver of quality performance and patient satisfaction in the health care context, which is in stark contrast to the manufacturing sector.

The purpose of this paper is to investigate the impact of hard total quality management (TQM) practices on operational performance dimensions in manufacturing organizations.

The study was designed in the Jordanian manufacturing sector. Organizations that are familiar with hard TQM practices specifically that had already implemented ISO 9001 certificate were randomly surveyed through structured questionnaire, yielded a sample of 40 responding organizations. Principal component factor analysis was used to analyze hard TQM practices implementation and organizations operational performance dimensions. As a result, specific hard TQM practices and operational performance dimensions were extracted. The hard TQM practices that significantly influence operational performance dimensions were tested using simple and multiple linear regression analysis.

The research findings showed that hard TQM practices in manufacturing sector include; continuous improvement, statistical process control (SPC), process management and quality tools and techniques. Meanwhile, operational performance dimensions include; quality and inventory management performance. Also, the findings showed that continuous improvement and SPC practices play a major role in obtaining the desired results of operational performance.

Three limitations can be identified in this research, using subjective measures of TQM practices and operational performance, low response rate and using a sample of organizations from various industries. This paper can help Jordanian manufacturing organizations to foster proper practices and make the right decisions related to operational performance.

This study describes a reliable hard TQM model that can be used by manufacturing organizations to improve their operational performance. Also, the results of this study contribute to prior literature and recommend some best practices for manufacturing organizations.

Total quality management (TQM) is a part of the total quality assurance perspective. This system, which is considered as a type of managerial philosophy, employs all organizational levels to constantly ameliorate the quality of goods and service. The purpose of this paper is to measure the effect of hard and soft TQM factors on the behavior of customers based on the role of innovation and continuous improvement.

The research model was extracted from TQM variables in hard and soft parts, customer behavior, innovation and continuous improvement by reviewing the literature and research background. Based on this, a questionnaire was prepared and then, distributed among the statistical population including 374 project managers, quality assurance managers as well as quality control managers by using simple random sampling. All sub-criteria of questionnaire were determined using Delphi technique, to test the research model. Having gathered the questionnaire, the hypotheses were analyzed by using structural equation modeling and AMOS software.

According to the statistical analyses, TQM has a significant effect on customer behavior through continuous improvement of the quality and innovation. Also, regarding the obtained results, the highest effect was related to the effect of hard TQM factors on customer behavior through innovation as 0.62. Furtheremore, TQM soft factors such as human resource management have significant effect on customer behavior through quality improvement and innovation. Moreover, TQM hard factors are effective on customer behavior through quality improvement and innovation.

The questionnaire was designed and distributed in order to evaluate the hypotheses in this study. One of the primary rationales behind utilizing this method instead of other methods such as interview was high geographical distribution of organizations. Using other moderator variables such as knowledge management, customer knowledge management and customer emotions can be conducted in the future in this area.

Changing the organizational relationships from task orientation to the process orientation, and controlling the organizational performance by measuring process innovations and improvements, while paying attention to the customer satisfaction system are suggested in this paper. These implications should be implemented in construction projects by department of project management office. Furtheremore, providing different communication for receiving the opinions of the customer and imposing them in the product and service, paying attention to the response system and customer complaint, implementation of this process in the organization, and having a process approach for presenting and developing services are the main subjects in this regard.

Unlike previous studies on this subject, a structural equation model is used for assessing unobservable latent constructs and their related interrelationship in measuring the impact of TQM factors. Focusing on customer behavior which is a broader domain than customer satisfation through continuous improvement of the quality and innovation is another value of this research.

Industry 4.0 or I4.0 has transformed the manufacturing landscape by integrating social and technical factors by means of the sociotechnical framework. However, the sociotechnical aspects of digitalization of total quality management (TQM 4.0), especially in small and medium enterprises (SMEs) remain largely unexplored. This groundbreaking research endeavors to delve into the pivotal role played by social (soft) and technical (hard) TQM 4.0 in driving I4.0 readiness among SMEs.

A research framework has been developed by harnessing the principles of Socio-technical systems (STS) theory. Data collection from a sample of 310 randomly selected SMEs manufacturing in Malaysia through an online survey approach. The collected data is then subjected to analysis using Partial Least Square-Structural Equation Modeling (PLS-SEM) through SmartPLS.

The study findings indicate that both hard and soft TQM 4.0 factors are vital to promoting I4.0 readiness (R² = 0.677) and actual implementation (R² = 0.216). Surprisingly, the findings highlight that customer-related construct has no impact on hard TQM 4.0 attributes. Furthermore, hard TQM 4.0 factors have played a partial mediating role on the relationship of soft TQM 4.0 and I4.0 attributes (20% = VAF = 80%).

This is a novel research as it explores the underexplored domain of sociotechnical aspects of TQM 4.0 within SMEs amid I4.0 transformation. The study distinctive contributes include revealing the pivotal role of both soft and hard TQM 4.0 factors in driving I4.0 readiness, emphasizing the primacy of people-related dimensions for successful implementation in manufacturing SMEs.

The purpose of the paper is to examine the binary character of total quality management (TQM) in food companies and to determine the impact of the two aspects of TQM – the “soft” and “hard” – on the quality management benefits.

A research project was carried out in 90 Greek food companies, using the questionnaire method. Two measurement models have been formulated. The first model includes the TQM philosophical elements and quality tools/techniques, while the second model includes the quality management benefits. Exploratory factor analyses are applied to extract the latent factors. The factors that significantly influence the quality management benefits are determined through multiple linear regression analyses.

The analysis of the models confirms the binary character of TQM (the “soft” and “hard” TQM elements) in food companies and the existence of internal and external quality management benefits. The “soft” TQM elements have a significant direct impact on quality improvement, employee benefits and customer satisfaction. However, the impact of the “hard” TQM elements on the above quality management benefits is not direct but indirect, through their significant correlation with the “soft” TQM elements. Finally, quality improvement is also a significant factor that directly influences employee benefits, customer satisfaction and business performance.

The small size of the sample of the responding food companies, the diversity of these companies and the subjective character of the data collected are limitations that suggest future research recommendations.

Food companies should realize the leading role of the “soft” aspect of TQM and the supporting role of the “hard” aspect in maximizing the quality management benefits and as a consequence in withstanding the current economic downturn.

Focusing on “quality-oriented” food companies that have ample experience in quality and food safety management systems, the present study reveals a significant direct impact of the “soft” TQM elements and an indirect impact of the “hard” TQM elements on the quality management benefits.

Effective total quality management (TQM) practices rely on the accurate classification of critical success factors (CSFs). The impact matrix cross-reference multiplication technique for classification (MICMAC) or/and fuzzy MICMAC (FMICMAC) can be used to identify key factors in the complex set. However, TQM includes both “hard” and “soft” factors, limiting application of the traditional MICMAC/FMICMAC method.

Previous literature on TQM was reviewed, CSFs were identified, and factors were sorted into soft and hard categories. The combined fuzzy integration and dual-aspect MICMAC (fuzzy dual-aspect MICMAC approach) was then applied to identify, cluster and prioritize the CSFs of TQM.

A total of 20 factors (10 soft and 10 hard) were identified and isolated to assess the manufacturing- and service-related TQM practices of the Pearl River Delta Region of China. Seven driver factors and one linkage factor emerged as the key CSFs that managers should prioritize.

A major limitation of this study is the dependency of the results on the definitions of linguistic labels. If the linguistic definitions of TQM CSFs do not closely correspond to the expert opinion data, then the analysis results may be inaccurate. Additionally, although expert opinions are utilized in the proposed method for comprehensive assessments, these opinions may influence the final results due to their inherent subjectivity.

A novel fuzzy dual-aspect MICMAC approach was developed to identify and classify CSFs for optimal TQM practices. This approach allows clustering of CSFs so that decision-makers can prioritize factors according to their dependence and driving powers. Practitioners should concentrate on the CSFs with higher driving powers for successful TQM.

This study aims to analyze how the interplay between hard and soft elements of total quality management (TQM) produces the conditions for sustaining success in the quest for quality.

A qualitative analysis (Gioia method) was carried out on an original dataset collected through both direct and indirect methods (i.e. archival sources, interviews and observations) to generate a new interpretive framework.

The interpretative framework identifies four categories of elements: trigger elements create the starting conditions for a quality virtuous cycle; benchmarking tools set the standards of performance; improvement tools enable exploration of the space of possible alternative practices and finally, catalytic forces allow the institutionalization of effective techniques discovered in this search process into new standards.

The findings the authors present in this paper are derived by a single case study, limiting the generalizability of our results in other settings.

This study has three implications: first, the design of trigger elements is critical for the success of any TQM initiative; second, the interplay of improvement and benchmarking tools at several levels should be coherent and third, to exploit the potential of TQM, efforts should be devoted to the dissemination of new effective practices by means of catalyzing elements.

The model provides a more specific understanding of the nature and purpose of the hard and soft elements of TQM and the dynamic interaction between the two classes of elements over time.

The purpose of this study is to map the implications and competencies for Industry 4.0 to the hard and soft aspects of total quality management (TQM).

The author/s collected data from purposively drawn samples of early-career engineering professionals (ECEPs) using a cross-sectional survey. A total of 20 ECEPs from three small-class cohorts (2014, 2016 and 2018) participated in the survey. The author/s analyzed data using the Kruskal–Wallis test and Wilcoxon–Mann–Whitney test to establish the effect of cohort and gender on the implications and competencies for Industry 4.0. The author/s then mapped the top- and bottom-ranked implications and competencies onto the hard and soft aspects of TQM using a matrix.

Based on the cohort, significant differences p < 0.05 existed in the interests and competencies for Industry 4.0. In congruence, the 2014 cohort had the highest number of “unique” top- and bottom-ranked competencies and implications spanning the hard and soft TQM. Based on gender, nonsignificant differences p < 0.05 existed in the interests and competencies for Industry 4.0. The male and female ECEPs' “common” top-ranked implications appeared under the hard and soft TQM. All their “common” top-ranked competencies appeared under the hard TQM, while all their “common” bottom-ranked competencies appeared under the soft TQM.

The sample size, context/discipline and perceptual data are limitations.

Optimizing an existing TQM framework/matrix to design Industry 4.0 TQM, advanced as TQM 4.0.

Perspectives of early-career professionals for TQM 4.0 implementation.