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Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

Air traffic resources mainly include two parts, namely, air traffic controller (ATC) and physical system resources, such as airspace. Reasonable assessment and effective management of ATC and airspace resources are the premise and foundation of ensuring the safety and efficiency of air traffic management systems. The previous studies focussed on subjective workload control and the statistics of control communication time; they revealed the lack of kinetic universality analyses of controlling actions. Although frequency distribution patterns were generated by controlling the timing sequence, the correlation between the controlling actions and terminal airspace (TMA) sector capacity was not revealed. The paper aims to discuss these issues.

Thus, given the immeasurable complexity of controlling actions and statistical features of the controlling communications, a dynamical model of ATC was built in this study to identify the frequency distribution patterns generated by controlling the timing sequence. With the Directorate of Operational and Analysis Task method, TMA sector capacity was estimated through multiple linear regression analysis.

With data from the Kunming sector, the power exponent was calculated as 2.55, and the mathematical expectation was determined to be 47.21 s. The correlation between controlling actions (workload) and sector capacity was obtained. Finally, the data were integrated in the verification of the model and its feasibility.

Airspace capacity is an index to measure the ability of the airspace system to deliver services to meet the air traffic demand. A scientific and accurate forecast of airspace capacity is a foundation of the effective management and rational allocation of the airspace resources. The study is of great significance for the efficient use of airspace resources, controller resources.

The purpose of this paper is to encourage administrators of device‐lending programs to leverage existing quantitative data for management purposes by integrating analysis of quantitative data into the day‐to‐day workflow.

This is a case study of NCSU Libraries' efforts to analyze and visualize transactional data to aid in the on‐going management of a device‐lending program.

Analysis and visualization of qualitative data related to technology lending revealed patterns in lending over the course of the semester, day, and week that had previously gone unrecognized. With more concrete data about trends in wait times, capacity lending, and circulation volume, staff are now able to make more informed purchasing decisions, modify systems and workflows to better meet user needs, and begin to explore new ideas for services and staffing models.

The concepts and processes described here can be replicated by other libraries that wish to leverage transactional data analysis and data visualization to aid in management of a device‐lending program.

Although much literature exists on the implementation and qualitative evaluation of device‐lending programs, this paper is the first to provide librarians with ideas for leveraging analysis of transactional data to improve management of a device‐lending program.

Airport capacity constraints lead to operational congestion and delays, which have become major threats to the aviation industry. They impose large costs on airlines and their passengers. Uncertainty in demand or unexpected events can cause a mismatch between capacity and demand, resulting in either capacity oversupply, with a decrease in efficiency, or airport congestion over an extended period. Moreover, airport capacity is rather difficult to define due to its multifaceted and dynamic nature, and it depends both on the available infrastructure and on operating procedures. Additionally, traditional capacity management methods do not consider relevant behavioral economic challenges to conventional analysis, particularly failure of the expected utility hypotheses and dependence of valuations on reference points. This study aims to develop a preliminary framework to include economic concepts when evaluating expansions of airport capacity.

This paper reviews major opportunities in airport demand and capacity management from an economic perspective while appraising the challenges involved in airport capacity expansion processes that have not been fully completely in past studies. Although welfare economics provides the conceptual foundations for demand/capacity analyses, the authors integrate the findings regarding capacity definition, uncertainty management and behavioral economics into standard economics to guide the measurement of the airport capacity expansion problem.

The authors obtain several insights regarding airport capacity and demand management. First, airport capacity is a complex metric when evaluating airport expansion, and it depends both on the available infrastructure and on operating procedures. Furthermore, airport throughput is highly conditioned by factors that shape capacity and delay and shows significant variability when these factors are modified. Second, a marginal change in capacity at congested airports may have a great impact on demand distribution, airline competition, aircraft types, fares, operating revenues, route map and other characteristics of a given airport. Behavior after capacity expansion is highly reliant on the slot allocation models. Additionally, overall social welfare is usually affected after changes in infrastructure in terms of increased connectivity, economic benefits and negative externalities, including noise and local pollution. Third, on-time performance is clearly nonlinear, and thus sensitive to variations in demand and capacity. Finally, airport capacity and demand management involve a trade-off between mitigating congestion and maximizing capacity utilization, so decision-making tools are required to support and enhance policy and managerial choices. Three main challenges arise when developing new methods for evaluating airport expansions: the definition of capacity, the management of uncertainty in demand and the need to consider economic concepts.

This paper explores and produces an in-depth understanding of the problem of airport capacity and demand balance. The authors propose a preliminary framework that considers the challenges that have been previously identified and that, particularly, provides an economic perspective for airport capacity expansion processes. This framework is completed with a theoretical model to help policymakers and airport operators when faced with a capacity development decision.

The objective of the research, and paper, is to determine first whether or not the accounting abstraction appears to dominate the manager’s perceptions of the physical reality of the firm’s utilization of its physical assets, and second, whether changes in the accounting abstraction (e.g. the addition of Capacity cost management reports and measurements) lead to changes in how managers perceive, and use, their physical assets. Using a cognitive decision-making structure developed by Wagenaar et al. (1995), this study explores the interplay between the structure and nature of capacity reporting (the surface structure of the decision) and the subsequent analysis and choice of managers within the firm (the deep structure of the decision). A five-site field research methodology was used to gather data from companies across a multitude of industry contexts and situations. Results suggest that the nature of capacity measurement and reporting does shape manager’s perceptions of current and potential future performance (the cognitive surface structure), with major implications for the nature and type of decisions and trade-offs made (the deep structure). Specifically, managers appear to make decisions that are illogical when considered in light of the physical reality of their operations based on the representations of this reality (e.g. the capacity measures and reports). Analysis and interpretation of these results suggest that what accounting makes visible appears to drive decision-making and performance in organization.

At roundabouts where entering traffic is required to give way to traffic circulating in the roundabout, the traffic capacity of each entry is a function of the flow of traffic circulating past it. This relationship has previously been analysed in two main ways: using a linear relationship based on regression and using a non-linear relationship based on a model of entering drivers' acceptance of gaps in the circulating traffic. The linear analysis has previously been extended to estimation of the reserve capacity or degree of overload of the roundabout as a whole in relation to a given pattern of approaching traffic. The non-linear analysis is extended similarly in this paper.

The relationships between entry capacity and circulating flow imply in turn that the capacity of each entry is a function of the entering flows and the proportions of traffic making various movements through the junction from some or all of the entries. Equations are established for determining derivatives of capacity or delay on each entry with respect to the demand flow for each movement. In particular, it is shown that when the roundabout is overloaded the capacity of an entry can depend upon the demand flow on that same entry, giving rise to a corresponding term in the derivative of the delay-flow relationship for the approach concerned.

Discusses the difficulties of measuring, defining and managing capacity; and develops a model which splits it into two components (resource and ability) plus several sub‐components, and recognizes the interfaces between them. Illustrates and defines the sub‐components and identifies three states of capacity loading: resource‐loaded (over‐resourced), ability‐loaded (e.g. over‐qualified staff) and even‐capacity (i.e. resources compatible with ability). Asserts that the relative capacities of firms within an industry form a “capacity curve” with ability‐loaded small firms, medium firms at even capacity and large firms resource‐loaded. Analyses 1994‐1997 data for the US electronics and electrical equipment industry to plot its capacity curve, explains the methodology used, and shows how the regression model can be applied to individual firms within the industry to improve capacity management. Recognizes the limitations of the study.

An important and challenging question for air transportation regulators and airport operators is the definition and specification of airport capacity. Annual capacity is used for long-term planning purposes as a degree of available service volume, but it poses several inefficiencies when measuring the true throughput of the system because of seasonal and daily variations of traffic. Instead, airport throughput is calculated or estimated for a short period of time, usually one hour. This brings about a mismatch: air traffic forecasts typically yield annual volumes, whereas capacity is measured on hourly figures. To manage the right balance between airport capacity and demand, annual traffic volumes must be converted into design hour volumes, so that they can be compared with the true throughput of the system. This comparison is a cornerstone in planning new airport infrastructures, as design-period parameters are important for airport planners in anticipating where and when congestion occurs. Although the design hour for airport traffic has historically had a number of definitions, it is necessary to improve the way air traffic design hours are selected. This study aims to provide an empirical analysis of airport capacity and demand, specifically focusing on insights related to air traffic design hours and the relationship between capacity and delay.

By reviewing the empirical relationships between hourly and annual air traffic volumes and between practical capacity and delay at 50 European airports during the period 2004–2021, this paper discusses the problem of defining a suitable peak hour for capacity evaluation purposes. The authors use information from several data sources, including EUROCONTROL, ACI and OAG. This study provides functional links between design hours and annual volumes for different airport clusters. Additionally, the authors appraise different daily traffic distribution patterns and their variation by hour of the day.

The clustering of airports with respect to their capacity, operational and traffic characteristics allows us to discover functional relationships between annual traffic and the percentage of traffic in the design hour. These relationships help the authors to propose empirical methods to derive expected traffic in design hours from annual volumes. The main conclusion is that the percentage of total annual traffic that is concentrated at the design hour maintains a predictable behavior through a “potential” adjustment with respect to the volume of annual traffic. Moreover, the authors provide an experimental link between capacity and delay so that peak hour figures can be related to factors that describe the quality of traffic operations.

The functional relationships between hourly and annual air traffic volumes and between capacity and delay, can be used to properly assess airport expansion projects or to optimize resource allocation tasks. This study offers new evidence on the nature of airport capacity and the dynamics of air traffic design hours and delay.