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The paper seeks to investigate decision‐making processes within hospital improvement activity, to understand how performance measurement systems influence decisions and potentially lead to unsuccessful or unsustainable process changes.

A longitudinal study over a 33‐month period investigates key events, decisions and outcomes at one medium‐sized hospital in the UK. Process improvement events are monitored using process control methods and by direct observation. The authors took a systems perspective of the health‐care processes, ensuring that the impacts of decisions across the health‐care supply chain were appropriately interpreted.

The research uncovers the ways in which measurement systems disguise failed decisions and encourage managers to take a low‐risk approach of “symptomatic relief” when trying to improve performance metrics. This prevents many managers from trying higher risk, sustainable process improvement changes. The behaviour of the health‐care system is not understood by many managers and this leads to poor analysis of problem situations.

Measurement using time‐series methodologies, such as statistical process control are vital for a better understanding of the systems impact of changes. Senior managers must also be aware of the behavioural influence of similar performance measurement systems that discourage sustainable improvement. There is a risk that such experiences will tarnish the reputation of performance management as a discipline.

Recommends process control measures as a way of creating an organization memory of how decisions affect performance – something that is currently lacking.

Outlines a model for the development of quality systems in New South Wales schools. Also considers quality assurance as a means of auditing such a system and the role of leadership in the development of such systems. Looks into the nature of quality systems and international quality standards. Notes the problems and challenges inherent in the introduction of a quality system concept into schools and suggests further research to look into leadership factors and training required to support such an introduction.

A survey of small businesses in Kentucky was conducted in the area of total quality management. The objective of the research was to determine the level of effort of small manufacturing firms in quality management and the degree to which their managers are currently guided by the TQM model as opposed to the economic conformance model. Preliminary results indicate the degree of penetration of the TQM philosophy and concepts among managers in small manufacturing firms. Also studied were the important elements in the operation and management of these firms that promote or discourage the successful implementation of TQM.

This paper develops a smart system based on the concept of Industry 4.0 to prevent customer dissatisfaction. The value of this prevention system is that it enables hoteliers to interact with customers by understanding what they like/dislike from their behaviors via data analysis. Therefore, this system helps hoteliers to enhance service quality by predicting service issues.

The system, named the dissatisfaction identification system (DIS), is developed. A total of 127 service items were examined by a hotel manager who preset the threshold values for the measurement of service quality. A big data set for the questionnaire survey is statistically generated by a pseudorandom number generator and 10,000 mock data sets are taken as input for comparison.

The results indicated that 36 out of 127 service items are identified as service issues for the participating hotel. Examples include customer code number 01d, “Space of parking lot is adequate” in the safety management category, and number 05a, “A hotel's service time meets my needs” in the front office service category. The items identified require improvement action plans for preventing customer dissatisfaction.

This paper offers a new perspective paper emphasizing customer dissatisfaction using a big data-driven technology system. The DIS, prevention system, is developed to aid hotels by enhancing their relationships with customers using a data-driven approach.