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The purpose of this study is to explore the relationship between total quality leadership, social capital development and organizational innovativeness in the school environment. While there are research studies focused on the impact of leadership on implementing quality management practices, innovation and organizational performance, the mediating effect of social capital development has not been explored on the influence of the school leaders.

To achieve the purpose of this study, data collected from 158 principals, who participated in the Teaching and Learning International Survey 2018, were analyzed using structural equation modeling.

This study found that total quality learning-oriented school leaders are supportive of developing social capital in their schools, and such social capital development is very useful to improve organizational innovativeness. Interestingly, social capital development has been found to mediate the relationship between total quality learning-oriented school leadership and organizational innovativeness.

This study submits evidence for two major activities that school leaders perform: learning- and control-oriented activities, both being important for improving and measuring quality in the educational sector. This study clearly shows that control-oriented activities lean toward negatively on social capital while learning-oriented activities strongly and positively influence social capital development. From this study, practitioners can be aware and consciously promote social capital development in schools and that social capital development mediates the influence of total quality leadership and innovation in schools.

Schools can be visualized as guarded communities for creating a secure environment for students in support of learning. This research study shows that the combined cognitive capital, structural capital and relational capital mediate the impacts of total quality leadership on innovativeness in schools. Thus, school leaders should first establish a mechanism to develop social capital among their employees to bring up innovative initiatives.

This paper deals with total quality management (TQM) with an emphasis on developing suitable strategies for improving quality and productivity in manufacturing systems. In recent years, TQM has been seen as an important strategy for achieving success in business both in terms of quality and productivity. However, there seem to be no clear strategic framework and guide‐lines for implementing TQM in manufacturing in the light of available advanced production concepts and technologies. A review of previous implementation approaches of TQM in practice has been presented in order to gain further insights into the implementation aspects of TQM. The main objective of this paper is to present a general framework for the development of TQM in manufacturing organizations considering the recent developments in production concepts and technologies and competitiveness among firms to utilize quality as a competitive weapon.

The ideas expressed in this work are based on those put into practice at the Okuma Corporation of Japan, one of the world′s leading machine tool manufacturers. In common with many other large organizations, Okuma Corporation has to meet the new challenges posed by globalization, keener domestic and international competition, shorter business cycles and an increasingly volatile environment. Intelligent corporate strategy (ICS), as practised at Okuma, is a unified theory of strategic corporate management based on five levels of win‐win relationships for profit/market share, namely: ,1. Loyalty from customers (value for money) – right focus., 2. Commitment from workers (meeting hierarchy of needs) – right attitude., 3. Co‐operation from suppliers (expanding and reliable business) – right connections., 4. Co‐operation from distributors (expanding and reliable business) – right channels., 5. Respect from competitors (setting standards for business excellence) – right strategies. The aim is to create values for all stakeholders. This holistic people‐oriented approach recognizes that, although the world is increasingly driven by high technology, it continues to be influenced and managed by people (customers, workers, suppliers, distributors, competitors). The philosophical core of ICS is action learning and teamwork based on principle‐centred relationships of sincerity, trust and integrity. In the real world, these are the roots of success in relationships and in the bottom‐line results of business. ICS is, in essence, relationship management for synergy. It is based on the premiss that domestic and international commerce is a positive sum game: in the long run everyone wins. Finally, ICS is a paradigm for manufacturing companies coping with change and uncertainty in their search for profit/market share. Time‐honoured values give definition to corporate character; circumstances change, values remain. Poor business operations generally result from human frailty. ICS is predicated on the belief that the quality of human relationships determines the bottom‐line results. ICS attempts to make manifest and explicit the intangible psychological factors for value‐added partnerships. ICS is a dynamic, living, and heuristic‐learning model. There is intelligence in the corporate strategy because it applies commonsense, wisdom, creative systems thinking and synergy to ensure longevity in its corporate life for sustainable competitive advantage.

One of the central tenets of total quality control is that responsibility for quality lies at the point of production. Salancik′s model of commitment is used to describe systems of work organisation which encourage employees to take on this responsibility. Commitment to quality can be fostered by managing the context within which production takes place. Management of the human aspects of total quality control may be informed by relevant ideas from the commitment literature.

Many organizations are investing much time and effort in the management of quality. A few enlightened ones even have a vision to be the best. G. Howland Blackiston, the president of the Juran Institute, noted recently that, “All around the world companies are waking up to ‘quality’. Everyone is touting quality. Many are attempting it. Some organizations have gotten enviable results by using the concepts of ‘managing for quality’ dramatically to lower their costs, increase their profits and become more competitive in an increasingly competitive market. For these winners, quality has become an integral part of their business strategy”.

The purpose of this study is to present a report on the development of an improved mathematical model for quantifying the cost of quality. In addition, a simulation model is developed using real-life industrial data; the model is used to investigate the impact of certain quality control level plans on cost of quality.

The cost of the quality model was developed based on the reported literature and suggestion from the company quality control manager. An extensive discussion was conducted with the quality control supervisors in the company to develop some quality control plans to investigate their impact on cost of quality. A simulation model that represents a specific section of the process at the company was used to carry out the investigation. The results were analysed and compared with some important findings reported in the literature that describe the characteristics of costs of quality.

The simulation work provides valuable insights into the behavior of the different components that constitute the total cost of quality. The results show that reduction of failure costs can be achieved at low or no-subsequent increase in the non-conformance expenditure. In addition, it seems that the traditional accounting system approach may no longer be adequate since it depends mainly on direct labour costs. The results indicate that the direct labour cost is only contributing by about 3 percent of the total cost of quality.

This paper focuses on the development of a comprehensive model for quantifying the cost of quality in a semiconductor company. Future research is needed to expand the model for more complex process configuration. In addition, the developed model could be extended to deal with variant defect rates.

This study presents an advanced theoretical model for cost quality that enhanced models of quality presented in the literature. Using the developed cost of the quality model, a comprehensive simulation was carried out to investigate the impact of some quality plans on cost of quality. The study clearly indicates important evidence to justify the implementation of cost of quality models in real-life industry.

Editorial This special issue of Industrial Management & Data Systems is a huge departure from our usual journal/ monograph style. This is an additional issue to the year's volume — a bonus in fact.

Reviews the strengths and weaknesses of quality control, quality assurance, total quality control and total quality management and shows how you can choose the quality management style which best fits your organisation′s needs. Compares approaches to quality management and articulates the differences between total quality management and the rest of the field. Argues that the choice of QM should fit an organization′s business strategy. Contends quality is a strategic issue, central to which is the management of change, which requires a diagnosis of where the organization is now. Suggests managers should look at what competitive advantage a particular approach will deliver for their organization and not at what has been delivered to other organizations.

A study of the effect of the dynamic process quality control on the economics of production and the Total System Cost (TSC) is dealt with. A mathematical model is presented for estimating the Economic Investment in Quality (EIQ) and the Economic Production Quantity (EPQ) in a multi‐stage production‐inventory system. The basic criterion considered for the determination of EIQ and EPQ is the minimisation of TSC. The TSC consists of (1) set‐up cost, (2) in‐process inventory carrying cost; this cost is a function of the processing time and the reset‐up time, (3) finished product inventory carrying cost, (4) reset‐up cost, (5) investment in quality control, and (6) scrappage cost. The feature of this research is to consider the aspect of dynamic process quality control, namely, “quality at the source”, by monitoring the quality of the product as the process continues and stopping the process if it goes out of control. A numerical example is given to illustrate the model.

While quality has been widely accepted as essential in today’s global competition, limited work has been conducted on the management processes that lead to it. This paper addresses the control processes in quality assurance and total quality management. The generic management control process is first presented and its deficiencies are highlighted. The paper then proposes control processes for quality assurance and total quality management. Finally, these two processes are compared.