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This study aims to examine the interrelationships among business process management (BPM), supply chain collaboration (SCC), collaborative advantage and organisational performance.

Data were collected from 204 manufacturing firms in Thailand, and the interrelationships proposed in the framework were tested via structural equation modelling.

This study highlights the role of intra- and inter-organisational practices and clearly demonstrates the joint role and impact of BPM and SCC, respectively. The results provide empirical evidence that BPM improves both organisational performance and collaborative activities. Also, SCC and collaborative advantage can have indirect positive impacts on organisational performance.

This work could be expanded by adopting a supplementary dyadic or extended supply chain (SC) approach and could also consider contextual factors, which were outside of the scope of this study.

The BPM approach has a positive impact on organisational performance, which is essential for collaborative activities between a firm and its SC partners. Further, effective BPM and SCC practices lead to enhanced performance and collaborative benefits. Practitioners should be better able to define and measure specific actions relating to their BPM and SCC practices.

This paper stresses the need to consider the interrelationships between BPM, SCC, collaborative advantage and organisational performance for both direct and indirect effects. Rather than focusing only on improvement at individual firm level, SCC is vital to compete in the market. Improving the effectiveness of SC allows higher organisational performance levels than those that could be achieved in isolation.

This paper aims to achieve a better understanding of the dissemination and adoption of quality management in China, in the context of theory on management trends and fashions, dissemination and adoption.

Following a literature review, the research adopts a qualitative, multiple case‐study approach, based on the study of six Shanghai manufacturers.

A dissemination and adoption model is presented, which contains nine observed dissemination and adoption factors. These factors and their relationships are identified, analysed and discussed.

The selection of case study companies was constrained by practical considerations of location and access. Further constraints of time and resource meant that only 14 interviews with managers from case‐study companies and three interviews with quality experts and consultants were conducted.

The findings will be of interest to those involved in developing QM within China, or working with Chinese manufacturing partners. They suggest that Chinese businesses do not blindly adopt QM initiatives simply because they are the current trend or fashion – instead, companies make decisions based on several rational adoption factors.

The research contributes to a richer understanding of the dissemination and adoption of QM in China, and extends understanding of QM dissemination in the context of management fashion and dissemination theories, using a qualitative approach.

The development of a quality database is central to effective automation of the operational activities of quality control. The importance of automation to quality data management is stated and a quality database structure outlined. The analysis and specification phase for a prototype system is discussed, with the functional requirements identified, and the choices of software, hardware and communications strategy described. Integration requirements with other computer systems are considered.

Many authors have suggested that disruption and associated costs result from poor quality performance in manufacturing. The purpose of this paper is to define and quantify the disruption costs associated with a simple manufacturing scenario using a simulation approach.

A manufacturing cell incorporating inspection and rework was simulated, and a validation exercise carried out. Using results from the simulation study, the authors then formulate the concept of a cost category for disruption cost, which is compatible with the traditional prevention‐appraisal‐failure (PAF) model for quality costs.

Comparative graphs of disruption costs and PAF costs elements are presented. The simulated disruption cost is compared with these traditional costs categories, and found to represent a significant additional cost at higher levels of non‐conformance.

The results presented in this paper are derived from a discrete‐event simulation exercise, using a model of a simplified generic manufacturing cell. They are believed to be indicative of costs that would occur in practical situations, but are not validated with empirical data. Further work would include such validation.

This is a theoretical paper, which attempts to extend a useful and well established cost model that has been widely accepted in industry.

The originality of this paper lies in the definition of the concept of disruption cost, as a separate category of quality cost. The simulation work indicates the potential size and behaviour of the disruption cost, compared with the traditional PAF costs categories.

The paper describes the methods of manufacturing process optimization, using Taguchi experimental design methods with historical process data, collected during normal production.

The objectives are achieved with two separate techniques: the Retrospective Taguchi approach selects the designed experiment's data from a historical database, whilst in the Neural Network (NN) – Taguchi approach, this data is used to train a NN to estimate process response for the experimental settings. A case study illustrates both approaches, using real production data from an aerospace application.

Detailed results are presented. Both techniques identified the important factor settings to ensure the process was improved. The case study shows that these techniques can be used to gain process understanding and identify significant factors.

The most significant limitation of these techniques relates to process data availability and quality. Current databases were not designed for process improvement, resulting in potential difficulties for the Taguchi experimentation; where available data does not explain all the variability in process outcomes.

Manufacturers may use these techniques to optimise processes, without expensive and time‐consuming experimentation.

The paper describes novel approaches to data acquisition associated with Taguchi experimentation.

Total quality management (TQM) has been applied widely in developed countries, and now appears to many as a precursor of the broader concept of business excellence. By contrast, in developing countries ISO 9000 series standards have been the focus of quality management development, and TQM is a new and challenging concept. TQM companies are rare, and with few exceptions are subsidiaries of larger multinational organisations. Examines the progress of four Thai SMEs attempting to implement TQM over a two‐year period, assisted by a facilitator and a “model company”. Relevant literature is briefly reviewed and issues of particular relevance to SMEs discussed. The efforts, problems, barriers and progress of the companies are described. The relative success of the companies was found to be related in large part to management and information issues, which are discussed.

The study of quality economics for manufacturing has focussed mainly on investments and costs, rather than attempting to quantify the benefits of improved quality in the market. This article presents an approach based on both costs and benefits. Systems dynamics‐based simulation has been employed with an optimisation technique, to identify quality spending levels which result in maximum overall profit. The simulation models are based on a Thai automotive manufacturer, which had employed Kaizen for many years, and hence this quality improvement approach was simulated. Two market conditions were modelled: fixed and variable‐price according to the market response to changes in quality level. Optimum profits were found at higher levels of quality spending than actual company spending. The paper examines the details of the optimum condition for the variable‐price market condition. Conclusions are drawn concerning quality improvement strategies and the potential effects of different market pricing conditions on optimum quality spending.