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This paper addresses the problem of bunching of buses and how it may be counter-acted. An algorithm is presented for providing selective priority to buses at traffic signals according to their headways, the highest levels of priority being given to those buses with the highest headways, i.e. those buses which are running late or falling behind the bus in front.

Alternative selective priority strategies are evaluated in terms of their effects on bus journey time regularity, bus delay and general traffic delay. A simulation model SPLIT (Selective Priority for Late buses Implemented at Traffic signals) has been developed to investigate the performance of different priority strategies. The paper describes the details of the model, including bus stop dwell times and overlapping bus services, and compares results obtained from the model for a number of different priority strategies.

This work was driven by the keen interest in bus priority applications in London within the EC DGVII project INCOME.

This paper aims to explore and analyse stakeholders’ perceptions of the development priorities and suggests more effective strategies to assist sustainable economic growth in the United Arab Emirates (UAE).

The authors use the World Bank data set, which collects various stakeholders’ opinions on the UAE development. First, the exploratory factor analysis has been applied to detect the main groups of development priorities. Second, the fuzzy cluster analysis has been conducted to detect the groups of stakeholders with different attitudes towards the importance of extracted groups of priorities. Third, clusters have been compared according to demographics, media usage and shared prosperity goals.

The two main groups of development priorities have been extracted by the exploratory factor analysis: economic priorities and sustainability priorities. Four clusters have been detected according to the level of motivation when it comes to the economic and sustainability priorities: Cluster 1 (High economic – High sustainability), Cluster 2 (High economic – Medium sustainability), Cluster 3 (High economic – Low sustainability) and Cluster 4 (Low economic – Low sustainability). Members of the cluster that prefer a high level of economic and sustainability priorities (Cluster 1) also prefer more diversified economic growth providing better employment opportunities and better education and training for young people in the UAE.

Limitations stem from the survey being conducted on a relatively small sample using the data collected by the World Bank; however, this data set allowed a comparison of various stakeholders. Future research should consider a broader sample approach, e.g. exploring and comparing all of the Gulf Cooperation Council (GCC) countries; investigating the opinions of the expatriate managers living in the UAE that are not from GCC countries; and/or including other various groups that are lagging, such as female entrepreneurs.

Several practical implications were identified regarding education and media coverage. Since respondents prioritize the economic development factors over sustainability factors, a media campaign could be developed and executed to increase sustainability awareness. A campaign could target especially male citizens since the analysis indicates that males are more likely to affirm high economic and low sustainability priorities than females. There is no need for further diversification of media campaigns according to age since the analysis did not reveal relevant differences in age groups, implying there is no inter-generational gap between respondents.

This paper contributes to the literature by comparing the perceived importance of various development goals in the UAE, such as development priorities and shared prosperity indicators. The fuzzy cluster analysis has been used as a novel approach to detect the relevant groups of stakeholders in the UAE and their developmental priorities. The issue of media usage and demographic characteristics in this context has also been discussed.

Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms.

To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created.

To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS.

Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance.

The purpose of this paper is to take forward consideration of context in health care priority setting and to offer some practical strategies for priority setters to increase receptiveness to their work.

A number of tools and methods have been devised with the aim of making health care priority setting more robust and evidence based. However, in order to routinely take and implement priority setting decisions, decision makers require the support, or at least the acquiescence, of key external parties. In other words, the priority setting process requires a receptive context if it is to proceed unhindered.

The priority setting process requires a receptive context if it is to proceed unhindered.

This paper develops the concept of legitimacy in the “authorising environment” in priority setting and describes strategies which might help decision makers to create a receptive context, and to manage relationships with external stakeholders.

Much research has been reported on the possibilities of using various heuristic priority rules to sequence batches through a job shop. The SPT (Shortest Priority Time) heuristic, or modifications to it, has been proved useful in many studies. This paper reports on the results obtained when simulating the work flow through a real machine shop. The simulation model has been used to test the effect on well known priority rules of releasing batches into the shop in order of decreasing expected throughput time. The important effect of this “phased release” of batches was to increase the percentage of batches delivered in finished parts stores on time, particularly in the case where priority rules were in use which might otherwise have resulted in poor delivery. This has important repercussions for management because it implies that by “phased” release of batches in the manner discussed, a large proportion of batches will be delivered on time whatever priority rule is in operation in the shop.

Traffic signal control is one of the oldest application areas of fuzzy sets in transportation. In general, fuzzy control is found to be superior in complex problems with multi-objective decisions. In traffic signal control, several traffic flows compete for the same time and space, and different priorities are often set to different traffic flows or vehicle groups

The public transport priorities are a very important part of the effective traffic signal control. Normally, the public transport priorities are programmed by using special algorithms, which are tailor-made for each intersection. The experiences have proved that this kind of algorithms can be very effective if some compensation algorithms and the traffic-actuated control mode are used. We believe that using the fuzzified public transport priority algorithms, the measures of effectiveness of traffic signal control can be even better. In this paper, our fuzzy control algorithm of the public transport priorities will be presented.

The purpose of this chapter is to describe a method for priority setting that can be used to identify options for disinvestment, and is also meant to serve as a tool for re-allocation of resources to achieve better outcomes with a given pot of resources.

This chapter draws on findings from the application of a priority setting and resource allocation framework known as Program Budgeting and Marginal Analysis (PBMA). Case studies are used to illustrate key points around implementation including factors for success and guidelines for improving priority setting in practice.

PBMA has been applied in over 150 settings over the last 30 years. Purposes varied from focusing strictly on disinvestment to examining opportunities for re-allocation. Many organizations report continued use of the framework and decision makers typically express a desire to not revert to historical allocation or political negotiation in deciding on the funding for programs.

Practical implications of this body of work on priority setting abound in that there are significant opportunities to improve resource allocation practice including better engagement of staff, clinicians and public members, greater use of evidence in decision making and improving process transparency.

As healthcare resources are limited, particularly in predominantly publicly funded health systems, prudent use of resources is critical. Actually applying the appropriate tools to ensure that funding aligns with organizational and system objectives is paramount.

Although there is a large body of literature on priority setting particularly in countries like the United Kingdom and Canada, this chapter serves to highlight key messages specifically in the context of fiscal constraint and in relation to the concept of disinvestment or service reduction.

It has been suggested that “space and artifacts constitute systems of communication which organizations build up within themselves” (Gagliardi, 1992a, b, p. vi) and reflect the cultural life within that organization. This is a study of how the “landscape” of a public library (“Library X”), as an information retrieval system, relates to the values of the people who created it. The efforts here are geared towards understanding the physical instantiation of institutional culture and, more specifically, institutional values as they are reflected through the artifact.