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The aim of this study is to investigate the effects of soft and hard quality management (QM) practices on innovation performance, considering innovation practices as a contextual variable mediating this relationship.

Using data from 132 Brazilian manufacturing companies, partial least square–structural equation modeling (PLS–SEM) is employed to test if soft and hard QM practices, directly, affect innovation practices and, indirectly, innovation performance. This investigation also aims to identify whether the relationships are maintained regardless of the size of the company.

The results suggest that soft QM has a positive effect on hard QM. However, only soft QM, not hard QM, has a significant effect on innovation practices. Additionally, soft QM has a significant positive effect on innovation performance through innovation practices. Company size does not influence the relationships.

The findings can help managers to adjust their managerial practices to enhance the effective impact of QM on innovation performance.

The previous literature presents conflicting results on the relationship between QM and innovation performance. Most studies have proposed a direct relationship between both constructs. This study considers innovation practices as a mediator in this relationship. Furthermore, this paper adds to the scarce literature reporting related studies conducted in developing countries.

This study aims to empirically investigate the effects of both soft and hard quality management (QM) on innovation and organizational performance. It also examines the mediating role of hard QM, administrative innovation and technical innovation on the relationship between soft QM and organizational performance in higher education (HE).

The approach of this study is quantitative. The data used to test the hypotheses were obtained through online questionnaire sent to the academic staff of public universities in Naples (Italy). The hypothesized relationships are tested with data collected from 356 respondents by using the partial least squares structural equation modeling technique (PLS-SEM).

The results show that quality practices improve innovation and organizational performance, while innovation positively impacts organizational performance. The findings also indicate that soft QM affects organizational performance directly and indirectly through hard QM. Hard QM and innovation show a partial sequential mediating effect on soft QM-performance relationship

In order to implement quality management properly in HE, directors need to recognize the different roles that soft and hard QM can have on innovation and organizational performance. It is important that higher education institutions (HEIs) allocate resources to establish both types of QM practices to achieve the effectiveness of the whole QM system.

Despite the existence of numerous studies on the relationship between QM, innovation and organizational performance in manufacturing and services, studies conducted in higher education are still few. This is one of the earliest studies that adopt the multidimensional approach of QM in HE which could help directors understand the interdependencies and different roles of soft and hard quality practices.

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.

This paper aims to investigate the effects of quality management practices (QMPs) on innovation in higher education (HE), and how organizational innovation (OI) may influence technical innovation.

The hypotheses were tested with partial least squares structural equation modeling on a sample of 449 valid responses by faculty members in Naples (Italy) public universities.

The findings support the interdependent relationships between QMPs and their positive impact on innovation. It was found that some QMPs impact on innovation through people and process management, and that OI predicts the technical one.

Directors should recognize the differences between QMPs to implement effective quality management (QM) strategy. Furthermore, they should combine technical and OIs.

Despite the existence of several studies on QM and innovation in manufacturing and services, there are only a few in HE. Based on a multi-dimensional QM approach, this paper investigates the different effects each QMP has on both the other QMPs and innovation in HE.

The purpose of this paper is to assess the role of business process innovation on the relationship between social quality management (SQM) and supply chain performance. To address this issue, this paper distinguishes SQM from soft quality management. This paper further refines the impact of two levels of business process innovation (radical vs incremental) on this relationship.

Data were collected through a survey of manufacturing firms throughout the USA. Hierarchical moderated regression analyses were performed in order to examine the hypotheses.

This study confirmed the positive association between SQM and supply chain performance. While the results confirm a positive moderating relationship with incremental business process innovation between SQM and supply chain performance, radical process innovation was found to have a negative moderating role on this relationship.

This paper distinguishes SQM from soft quality management thus making it easier to determine which aspects of soft quality management enhance supply chain performance. This study also provides evidence of the differing ways in which business process innovation moderates the relationship between SQM and supply chain performance specifically identifying the positive and negative moderating role of incremental and radical business process innovations.

This study aimed to investigate the impact of total quality practices on knowledge management (KM) processes across a Social Security Corporation (SSC) in Jordan and explore the best approach to improve KM processes using quality management.

This study followed a quantitative methodology: a conceptual model was developed based on an extensive review of the related literature; an online survey was developed and distributed using the SSC's intranet; and 384 surveys were completed and used in the statistical analysis. The two-stage approach of structural equation modeling (SEM) was employed to analyze and interpret the data, and was used to validate the conceptual model of this research.

Based on the statistical analysis it was found that six out of seven independent factors relating to quality management practices were confirmed to have a significant impact on the knowledge management processes (KMPs). Building upon the findings an agenda for improving KM processes using quality management is proposed.

This study was conducted in one organization namely the SSC because it is the largest public service organization in Jordan and offers compulsory services. The inclusion of other public organizations and companies may reflect different findings. Future research may collect data from other service industries to get a more comprehensive perspective from developing countries such as Jordan. Moreover, the population of this study included only the General Director, General Director Assistants, and Administrative Managers. Front-line employees were excluded from the data collection because the study was conducted solely from a managerial perspective.

The purpose of this paper is to investigate the key “hard” and “soft” quality management factors used by Australian small and medium enterprises (SMEs) and their association with organisational performance.

A survey questionnaire was constructed for this research using Powell's quality management framework. The respondents were required to indicate their degree of implementation of quality management practices and to rate their TQM performance in relation to overall performance, return on assets, market share and customer satisfaction.

The study found that improved overall performance appears to be favourably influenced by a combination of “hard” TQM factors such as benchmarking and quality measurement, continuous improvement, and efficiency improvement; and the “soft” TQM factors consisting of top management philosophy and supplier support, employee training and increased interaction with employees and customers. Furthermore, the TQM factors of employee training, efficiency improvement, and employee and customer involvement would appear to be important in maintaining customer satisfaction, whilst employee and customer involvement also appeared to be important in maintaining a competitive edge in terms of return on assets.

The findings show that it is necessary to focus on a combination of soft or behavioural aspects and the hard “systems‐oriented” aspects of QM to achieve an improvement in overall performance, and that to maintain customer satisfaction and return on assets it is just as important to focus on employee involvement and training, as it is to have a customer focus.

The purpose of this paper was to modify an existing survey that measures co-worker perceptions of health-related quality management (QM) values and perceived health and to measure both co-worker and manager perceptions of those values. The purpose was also to test the modified survey and then compare the results from managers and co-workers from two organizations in which the survey has been used to measure baseline data in a lean research project and to help managers understand the areas where improvement is needed.

An earlier survey measuring co-worker perception of the dimensions of the health-related QM values “leadership commitment” and “participation of everybody” has been developed with corresponding statements for managers. The results of the survey were analyzed using SPSS (Statistical Package for the Social Sciences), the Cronbach’s alpha coefficient was calculated for each of the dimensions, and the correlations between the dimensions and the health index were investigated using the Pearson correlation. The mean and standard deviation were also calculated.

The modified survey is presented in the paper, and the results demonstrate that the managers’ perception of the presence of health-related QM values is higher than that of the co-workers. Seeing the leadership from the co-workers’ standpoint compared with the managers’ perspective provides novel insight for both the researcher and the managers.

Leaders in organizations must develop greater efficiency to improve operational performance and develop healthy work environments. Practicing QM can benefit performance and is central for inspiring quality and efficiency within organizations, as well as for enhancing co-worker well-being. Earlier research found relationships between co-workers’ perception of their health and the health-related QM values “leadership commitment” and “participation of everybody.” With the survey presented in this paper, it is possible to measure these health-related QM values and provide a comparison between manager and co-worker perceptions.

The purpose of this paper is to explore the relationship between quality management (QM) and performance, specifically how the infrastructure and core QM practices affect quality and business performance, in Indian manufacturing organizations.

In this study, the empirical data were drawn from 262 manufacturing organizations in India. The research model was tested using the structural equation modeling technique.

The findings of the empirical study revealed that infrastructure QM practices have a positive effect on core QM practices and indirectly on quality performance, whereas, core QM practices have a positive effect on quality performance. Also, quality performance has a positive effect on business performance.

This study considered QM from two dimensions (infrastructure and core quality practices), the study further contributes to the understanding of the different roles played by diverse QM dimensions in determining business performance in terms of increased return on investment, shareholder and stakeholder value.

The study showed that infrastructure quality practices support the application of core quality practices. Therefore, managers must develop and maintain their organization’s quality system and sufficient resources need to be allocated to both types of practices in order to achieve the superior business performance.

This study considers both total quality management and Six Sigma practices for defining a new set of infrastructure and core QM practices in Indian manufacturing organizations.

A thorough analysis of nonlinear relationships between quality management (QM) and organizational outcomes has largely been ignored in the current empirical QM literature, which can have profound theoretical and managerial implications. The existence of nonlinear relationships implies taking a contingent view in that QM practices are more effective depending on their level of implementation in an organization. The purpose of this paper is to focus on this possibility and undertake an in-depth study of the sparse nonlinear relationship suggested by the literature.

The authors introduce an empirical study carried out on a sample of 168 service firms belonging to sectors experienced in QM and, through polynomial regression analysis, identify the nature of the relationship between QM and financial performance (return on assets).

The results, by showing an S-shaped curve, support a nonlinear association between these two variables. The presence of this functional form provides a satisfactory solution to the growing debate among researchers who, from a linear perspective, defend the positive effects of QM on organizational outcomes, those who find no significant effect, and still others who claim that QM has a negative effect.

The results show that in organizations with a low level of QM implementation, managers should increase investment in QM, even though this increase will not be correspondingly beneficial in the same proportion. In contrast, in organizations with a high level of QM implementation, managers are advised to reflect on undertaking projects that represent an additional investment in QM, with the aim of finding their optimal level.