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Truck appointment systems have been applied in critical container ports in the United States due to their potential to improve handling operations. This paper aims to develop a truck appointment system to optimise the total cost experiencing at the entrance of container terminals by managing truck arrivals and the number of service gates satisfying a given level of service.

The approximation of M_t/G/n_t queuing model is applied and integrated into a cost optimisation model to identify (1) the number of arrival trucks allowed at each time slot and (2) the number of service gates operating at each time slot that ensure the average waiting time is less than a designated time threshold. The optimisation model is solved by the Genetic Algorithm and tested with a case study. Its effectiveness is identified by comparing the model's outcomes with observed data and other recent studies.

The results indicate that the developed truck appointment system can provide more than threefold and twofold reductions of the total cost experiencing at the terminal entrance compared to the actual data and results from previous research, respectively.

The proposed approach provides applicably coordinated truck plans and operating service gates efficiently to decrease congestion, emission and expenses.

The purpose of this study is to examine the impact of competing logics on the implementation of risk-based management controls (RBMC) by providing evidence of resistance due to competing logics. Moreover, the study proposes solutions to logic contestation. These solutions may help the company override logic complexity.

This study draws upon the theory of institutional logics. It adopts an interpretative qualitative research approach and uses the case study method. Data were collected from one of the biggest private sector insurance companies in Egypt through a triangulation of interviews, observations and documents.

We found that internalised and institutionalised roles and structures – represented by the incumbent corporate and community-related sets of logics – compete and disrupt the emerging enterprise risk management and RBMCs. The newly imposed RBMCs produced heterogenic practices that changed the means of controls at the case company. However, this change was faced by resistance from local employees, as it represented a challenge to the prevailing cultural symbols and norms in their traditional work environment.

This study contributes to the literature by offering new evidence on resistance to Western risk-based management control projects applied in emerging markets. Moreover, it extends the cultural political economy of management accounting and control by illustrating that management accounting in emerging markets is also an operational manifestation of culture, community and location.

Airports are limited in terms of capacity. Particularly, runways can only accommodate a certain number of movements (arrivals and departures) while ensuring safety and determined operational requirements. In such a constrained operating environment, any reduction in system capacity results in major delays with significant costs for airlines and passengers. Therefore, the efficient operation of airports is a critical cornerstone for demand and delay management of the whole air transportation system. Runway scheduling deals with the sequencing of arriving and departing aircraft at airports such that a predefined objective is optimized subject to several operational constraints, like the dependency of separation on the leading and trailing aircraft type or the runway occupancy time. This study aims to develop a model that acts as a tactical runway scheduling methodology for reducing delays while managing runway usage.

By considering real airport performance data with scheduled and actual movements, as well as arrival/departure delays, this study presents a robust model together with an optimization algorithm, which incorporates the knowledge of uncertainty into the tactical operational step. The approach transforms the planning problem into an assignment problem with side constraints. The coupled landing/take-off problem is solved to optimality by exploiting a time-indexed (0, 1) formulation for the problem. The Binary Integer Linear Programming approach allows to include multi-criteria and multi-constraints levels and, even with some major simplifications, provides fewer sequence changes and target time updates, when compared to the usual approach in which the plan is simply updated in case of infeasibility. Thus, the use of robust optimization leads to a protection against tactical uncertainties, reduces delays and achieves more stable operations.

This model has been validated with real data from a large international European airport in different traffic scenarios. Results are compared to the actual sequencing of flights and show that the algorithm can significantly contribute to the reduction of delay, while adhering as much as possible to the operative procedures and constraints, and to the objectives of the airport stakeholders. Computational experiments performed on the case study illustrate the benefits of this arrival/departure integrated approach: the proposed algorithm significantly reduces weighted aircraft delay and computes efficient runway schedule solutions within a few seconds and with little computational effort. It can be adopted as a decision-making tool in the tactical stage. Furthermore, this study presents operational insights regarding demand and delay management based on the results of this work.

Scheduling arrivals and departures at runways is a complex problem that needs to address diverse and often competing considerations among involved flights. In the context of the Airport Collaborative Decision Making programme, airport operators and air navigation service providers require arrival and departure management tools that improve aircraft flows at airports. Airport runway optimization, as the main element that combines airside and groundside operations, is an ongoing challenge for air traffic management.

Weather events have a significant impact on airport arrival performance and may cause delays in operations and/or constraints in airport capacity. In Europe, almost half of all regulated airport traffic delay is due to adverse weather conditions. Moreover, the closer airports operate to their maximum capacity, the more severe is the impact of a capacity loss due to external events such as weather. Various weather uncertainties occurring during airport operations can significantly delay some arrival processes and cause network-wide effects on the overall air traffic management (ATM) system. Quantifying the impact of weather is, therefore, a key feature to improve the decision-making process that enhances airport performance. It would allow airport operators to identify the relevant weather information needed, and help them decide on the appropriate actions to mitigate the consequences of adverse weather events. Therefore, this research aims to understand and quantify the impact of weather conditions on airport arrival processes, so it can be properly predicted and managed.

This study presents a methodology to evaluate the impact of adverse weather events on airport arrival performance (delay and throughput) and to define operational thresholds for significant weather conditions. This study uses a Bayesian Network approach to relate weather data from meteorological reports and airport arrival performance data with scheduled and actual movements, as well as arrival delays. This allows us to understand the relationships between weather phenomena and their impacts on arrival delay and throughput. The proposed model also provides us with the values of the explanatory variables (weather events) that lead to certain operational thresholds in the target variables (arrival delay and throughput). This study then presents a quantification of the airport performance with regard to an aggregated weather-performance metric. Specific weather phenomena are categorized through a synthetic index, which aims to quantify weather conditions at a given airport, based on aviation routine meteorological reports. This helps us to manage uncertainty at airport arrival operations by relating index levels with airport performance results.

The results are computed from a data set of over 750,000 flights on a major European hub and from local weather data during the period 2015–2018. This study combines delay and capacity metrics at different airport operational stages for the arrival process (final approach, taxi-in and in-block). Therefore, the spatial boundary of this study is not only the airport but also its surrounding airspace, to take both the arrival sequencing and metering area and potential holding patterns into consideration.

This study introduces a new approach for modeling causal relationships between airport arrival performance indicators and meteorological events, which can be used to quantify the impact of weather in airport arrival conditions, predict the evolution of airport operational scenarios and support airport decision-making processes.

This paper aims to propose an expatriate psychological adjustment model that postulates expatriate mental health as an antecedent to psychological adjustment. It presents novel predeparture and post-arrival international human resource management (IHRM) expatriate management mental health supportive interventions.

This paper critically reviews theoretical frameworks in the IHRM domain around expatriate psychological adjustments such as the U-Curve Adjustment Theory (Lysgaard, 1995), the Framework of International Adjustment (Black et al., 1991), the Dimensions of Expatriate Adjustment (Haslberger et al., 2013) and the Stress Outcome Model (Bader and Berg, 2014), in a quest to develop a new conceptual framework. This study presents a new conceptual framework along with propositions to take into consideration the relationship between mental health and expatriates' psychological adjustment.

The findings suggest that mental health is an antecedent paramount to psychological adjustment. The paper proposes mental health-supportive IHRM expatriate management interventions to address the potential failure of expatriates' psychological adjustment. The authors elaborate on the IHRM expatriate management policies and practices at the home and host country to ensure the mental health of company-assigned expatriates sent on international assignments.

The novel conceptual framework underpins mental health as the antecedent paramount to expatriate adjustment, taking into consid eration the elevated stress of situational events such as COVID-19, which had previously not received substantive formal consideration by research scholars in the IHRM domain. The conceptual framework encourages the inclusion of mental health as an antecedent in future research.

The use of the 4D trajectory operational concept in the future air traffic management (ATM) system will require the aircraft to meet very accurately an arrival time over a designated checkpoint. To do this, time intervals known as time windows (TW) are defined. The purpose of this paper is to develop a methodology to characterise these TWs and to manage the uncertainty associated with the evolution of 4D trajectories.

4D trajectories are modelled using a point mass model and EUROCONTROL’s BADA methodology. The authors stochastically evaluate the variability of the parameters that influence 4D trajectories using Monte Carlo simulation. This enables the authors to delimit TWs for several checkpoints. Finally, the authors set out a causal model, based on a Bayesian network approach, to evaluate the impact of variations in fundamental parameters at the chosen checkpoints.

The initial results show that the proposed TW model limits the deviation in time to less than 27 s at the checkpoints of an en-route segment (300 NM).

The objective of new trajectory-based operations is to efficiently and strategically manage the expected increase in air traffic volumes and to apply tactical interventions as a last resort only. We need new tools to support 4D trajectory management functions such as strategic and collaborative planning. The authors propose a novel approach for to ensure aircraft punctuality.

The main contribution of the paper is the development of a model to deal with uncertainty and to increase predictability in 4D trajectories, which are key elements of the future airspace operational environment.

This research constructs the critical predictors of visitation that shall allow the practitioners to foresee the visitation in the years to come through secondary data. For this study, tourist arrival data associated with the most popular forest park (i.e., Xiton Forest Park) in Taiwan along with relevant socio-economic data are utilized. This research adopts a group of analytical procedures involving correlation analysis, regression, and curve estimation analyses. The results show that the number of holiday per month and the average monthly rainfall have positive and negative correlations, respectively, with the visitation. Meanwhile, average monthly temperature and monthly gross domestic product per capita show a positive correlation in all three analytical methods and therefore are regarded as the primary predictors of tourist arrival. Consequently, this study provides managerial implications to increase the tourist arrivals to the forest park.

This report aims to present a detailed evaluation of resilience planning of the ASEAN-5 tourism sector to national disasters. The project analyses the challenges to the tourism industry in the ASEAN-5 (Singapore, Indonesia, Thailand, the Philippines and Malaysia) countries due to national disasters (economic crisis, health hazards, natural calamity and/or act of terrorism) and the effectiveness of the measures taken in response to disastrous events.

The project analyses the effect of national disasters over a 10-year period in the ASEAN-5 countries on tourism economy and effectiveness of government action in resilience planning. The study uses two research questions to comment on comparative effectiveness of resilience planning in the ASEAN-5 nations.

The findings of this study revealed that national disasters affect a county’s tourism sector performance and its economy negatively. In particular, national disasters have harmful effects for a country’s tourism arrivals, tourism receipts, gross domestic product and unemployment. The findings reveal that regardless of geographical closeness of the ASEAN-5 countries, each experienced different effects in terms of national disasters and each used different government recovery measures.

This paper builds a knowledge management system for national disasters and the tourism sector. It provides a ready reference of timeliness and effectiveness of measures and to develop a framework for future tourist disaster management systems. Specifically, the relationships between the tourism indicators explored in this study contribute significantly to the knowledge on how these indicators interact to affect the tourism industry and the country’s economy. Furthermore, this information would act as a guide for countries to design and implement resilience planning and disaster management response.

Resilience planning is emerging as a key area under sustainable development. This report presents an evaluation of resilience planning of the ASEAN-5 tourism sector to national disasters.

The current air traffic management (ATM) operational approach is changing; “time” is now integrated as an additional fourth dimension on trajectories. This notion will impose on aircraft the compliance of accurate arrival times over designated checkpoints (CPs), called time windows (TWs). This paper aims to clarify the basic requirements and foundations for the practical implementation of this functional framework.

This paper reviews the operational deployment of 4D trajectories, by defining its relationship with other concepts and systems of the future ATM and communications, navigation and surveillance (CNS) context. This allows to establish the main tools that should be considered to ease the application of the 4D-trajectories approach. This paper appraises how 4D trajectories must be managed and planned (negotiation, synchronization, modification and verification processes). Then, based on the evolution of a simulated 4D trajectory, the necessary corrective measures by evaluating the degradation tolerances and conditions are described and introduced.

The proposed TWs model can control the time tolerance within less than 100 s along the passing CPs of a generic trajectory, which is in line with the expected future ATM time-performance requirements.

The main contribution of this work is the provision of a holistic vision of the systems and concepts that will be necessary to implement the new 4D-trajectory concept efficiently, thus enhancing performance. It also proposes tolerance windows for trajectory degradation, to understand both when an update is necessary and what are the conditions required for pilots and air traffic controllers to provide this update.

The purpose of this paper is to develop an enhanced framework for workforce management in a modern call center environment, called the consecutive staffing using simulation (CSS) approach. The paper aims to investigate the value of a time‐dependent approach to determine staffing levels without making an assumption that call centers to be a queuing model in a steady state.

Staffing is usually accomplished through the use of simple queuing models, Erlang‐C (M/M/c). It is common to adopt a stationary independent period by period (SIPP) approach. However, staffing based on SIPP does not consider uncompleted calls and each planning interval cannot achieve a steady state in most cases, since the lengths of planning intervals are short in fact. In this context, the CSS approach considers uncompleted calls and determines staffing levels by using simulation.

Staffing based on the CSS approach needed fewer agents, compared with staffing based on the SIPP approach. Hiring less agents during a single planning horizon lead to a decrease in total operational costs for the call center. Staffing based on SIPP became less accurate when the average service duration became longer or the arrival rate fluctuation was large, which often occurred in the morning and around lunch break.

The CSS approach is based on the dynamic staffing proposed by Whitt. However, CSS extends the basic idea of dynamic staffing to combine a simulation experiment with a number of repetitions and the same run length of planning intervals. In a call center with shorter planning intervals, management should adopt staffing based on CSS for accurate planning and updating of staffing levels during a single planning horizon.