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Based on the existing provisions/operations of tsunami warning in the Indian Ocean, authors observed that detection as well as arrival time estimations of regional tsunami service providers (RTSPs) could be improved. In particular, the detection mechanisms have been eccentrically focussed on Sunda and Makran tsunamis, although tsunamis from Carlsberg ridge and Chagos archipelago could generate devastating tsunamis for which inadequate provisions exist for detection and arrival time/wave height estimation. RTSPs resort to assess estimated arrival time/wave heights from a scenario-based, pre-simulated database. These estimations in terms of Sri Lanka have been found inconsistent. In addition, current warning mechanism poorly manages non-seismic tsunamis. Thus, the purpose of this study is to investigate these drawbacks and attempt to carve out a series of suggestions to improve them.

The work initiated with data retrieved from global earthquake and tsunami databases, followed by an estimation of probabilities of tsunamis in the Indian Ocean with particular emphasis on Carlsberg and Chagos tsunamis. Second, probabilities of tsunami detection in each sub-region have been estimated with the use of available tide gauge and tsunami buoy data. Third, the difficulties in tsunami detection in the Indian Ocean are critically assessed with case studies, followed by recommendations to improve the detection and warning.

Probabilistic estimates show that given the occurrence of a significant earthquake, both Makran and Carlsberg/Chagos regions possess higher probabilities to harbour a tsunami than the Sunda subduction zone. Meanwhile, reliability figures of tsunami buoys have been declined from 79-92 to 68-91 per cent over the past eight years. In addition, a Chagos tsunami is left to be detected by only one tide gauge prior to it reaching Sri Lankan coasts.

The study uses an averaged tsunami speed of 882 km/h based on 2004 Asian tsunami. However, using exact bathymetric data, Tsunamis could be simulated to derive speeds and arrival times more accurately. Yet, such refinements do not change the main derivations and conclusions of this study.

Tsunami detection and warning in the Indian Ocean region have shown room for improvement, based on the inadequate detection levels for Carlesberg and Chagos tsunamis, and inconsistent warnings of regional tsunami service providers. The authors attempted to remedy these drawbacks by proposing a series of suggestions, including a deployment of a new tsunami buoy south of Maldives, revival of offline buoys, real-time tsunami simulations and a strategy to deal with landslide tsunamis, etc.

Indian Ocean is prone to mega tsunamis as witnessed in 2004. However, more than 50 per cent of people in the Indian Ocean rim countries dwell near the coast. This is verified with deaths of 227,898 people in 14 countries during the 2004 tsunami event. Thus, it is of paramount importance that sufficient detection levels are maintained throughout the Indian Ocean without being overly biased towards Sunda tsunamis. With respect to Sri Lanka, Makran, Carlesberg or Chagos tsunamis could directly hit the most populated west coast and bring about far worse repercussions than a Sunda tsunami.

This is the first instance where the threats from Carlesberg and Chagos tsunamis to Sri Lanka are discussed, probabilities of tsunamis are quantified and their detection levels assessed. In addition, reliability levels of tsunami buoys and tide gauges in the Indian Ocean are recomputed after eight years to discover that there is a drop in reliability of the buoy data. The work also proposes a unique approach to handle inconsistencies in the bulletins of regional tsunami service providers, and to uphold and improve dwindling interest on tsunami buoys.

This paper aims to apply network modelling and simulation methods to critically analyse the tornado detection, warning and communication system in the Canadian Prairies.

The simulation results of the developed network illustrate the role of collaborating partners and provide a probabilistic representation of the overall time from tornado detection to warning issuance. Furthermore, the total time from the warning issuance to when evacuation is complete is analysed by combining the time distribution of the network and the evacuation time distribution, which is developed based on survey data.

A set of recommendations are offered as guidelines for consideration and possible adoption by collaborating partners who are involved at different stages of the detection, warning, communication and evacuation process.

The research contributes to a deeper understanding of the pre-disaster phase of tornadoes by providing an overall analysis that spans different areas under the general umbrella of disaster mitigation.

This research paper helps the community to work together in developing mitigation measures to enhance social values and benefits.

This paper shows how activity network modelling and simulation methods, which are normally applied in construction management, can be used to analyse the overall process from tornado detection to the warning issuance.

This paper attempts to assess the transit service reliability with taking into account the interaction between network performance and passengers' travel choice behaviors. Besides the well-known schedule reliability, a waiting-time reliability is newly defined as the probability that the passengers' average waiting time is less than a given threshold. A Monte Carlo simulation approach, which incorporates a stochastic user equilibrium transit assignment model with explicit capacity constraints and elastic frequencies, is proposed to estimate the above two reliability measures of transit service. A numerical example is used to illustrate the applicability of the reliability measures and the proposed approach.

Assessing airport service performance requires understanding of all passenger processing and discretionary activities at airport passenger terminals – a need that has not yet been addressed in the research to date. This paper aims to address this shortcoming in evaluating overall airport service based on passenger experience from departure to arrival.

Comparative analysis over 40 airport models, including their indicators and configuration of service measures, was undertaken in a previous work to identify key-design requirements in assessing airport service performance based on passenger experience (Wiredja et al., 2015). Based on these requirements, this paper constitutes the development of a passenger-centred model covering all service areas from departure to arrival terminals. The newly developed model is then examined using factor and regression analyses by involving 215 airline passengers from 22 world’s international airports.

Overall service performance is understood as a function of combined sub-performances of two groups of airport domains: processing domains and non-processing domains. The overall result demonstrated that the two sets of service factors and their relevant attributes had significant impact on overall service performance at processing and non-processing domains.

The proposed model applies a set of dynamic performance measures that provide flexibility. These measures are adjustable depending on the needs. Adding or replacing measures defines the specificity of the domains and performances assessed. The model components can be modified in respective service attributes when passenger needs or priorities change. The only constant component is user-centred indicators (in this research, Passenger-centred indicators).

This research has generated new insights and knowledge that directly contribute to the assessment of airport service performance. The novelty of this research is the development of a passenger-centred approach in evaluating overall airport service based on passenger experience. This passenger-driven model provides a more integrated and robust approach in this field than previously available.

The purpose of this paper is to provide a comprehensive overview of the literature related to performance measurement (PM) in airport settings. Two research questions were addressed: how the literature has evolved during the last 45 years; and which performance dimensions have been emphasized during this period.

For the purpose of this study, 380 documents, published between 1970 and 2015 were systematically analyzed. The literature reviewed comprises academic peer-reviewed articles, and studies published by other relevant sources, including professional-related literature.

The literature reviewed points to three stages relating to the evolution of the PM in airport settings during the period analyzed. Although with a significant lag, this evolution seems to have followed the broad literature on PM. Moreover, a relationship between these stages and the changes occurring at the airport industry was found. Several aspects of airport multidimensional performance are identified and discussed.

Based on the findings of this study, it is concluded that a more comprehensive approach to airport PM is needed. In this context, a research agenda is suggested.

The findings of this study have relevant practical implications for the airport industry. In this context, a framework representing a comprehensive approach to airport performance dimensions with impact on external stakeholders is presented. This framework can be a relevant contribution for researchers and practitioners which are looking for a more comprehensive and multidimensional approach to airport PM.

To the best of the authors’ knowledge, this study appears to be the first to examine the literature related to airport PM according to such a comprehensive approach. A framework of the performance dimensions related to the airport business is provided.

Global issues on the environment, such as climate change, air pollution and carbon monoxide emission, are the primary concerns in any part of the world. The purpose of this paper is to construct a conceptual framework for the travel behavior performance of a commuter, and it is expected to mitigate air pollution from vehicle emission and to promote smart mobility on the road.

From the extensive literature review, the conceptual framework for the travel behavior performance of a commuter has been developed and is supported by the theory of interpersonal behavior (TIB), whose functions are attitude, social factor, affect and habit. In the present paper, attitude is conceptualized by four predictors, namely confidence in driving, green environment, social responsibility and deviation in driving. The social factor is characterized by subjective norms, social status and digitalization. Affect factor is conceptualized by accidents and damages, road infrastructure, and weather conditions. The mental block in following the ancestor’s way of owning a personal vehicle is the predictor for the habit.

One of the major contributors to environmental damages is road traffic. Notably, vehicle emissions are on the rise every year due to the increase of reliance on vehicles, and there is no alternative to this issue. Although Malaysia has a well-organized infrastructure with effective digitalized technology on the road for the transport system, there is severe traffic congestion in Klang Valley, Kuala Lumpur, because of a lack of travel plan behavior during peak hours. If the road commuters give the predictors constructed in the proposed conceptual framework the highest importance, then there will be much relief to traffic congestion on the road.

Since the present study focuses on the conceptualization of an urban travel behavior model (UTBM), and also highlights the synchronization of the proposed framework with the management theory, the results are expected after the primary survey based on the cross-sectional study will be conducted.

The identification of the suitable predictors for the UTBM toward the travel behavior performance of a commuter is the real novelty of the present study. Also, the cause and effect relationships of different predictors in terms of path directions of the proposed research framework are the highlights of the study. Further, the predictors in the proposed framework and the TIB have been synchronized with operational definitions, which are the original contributions of the present study, which will enhance the sustainable environmental development for the society as a whole.

Considering the complexity of the airport industry service palette, it is important to identify which air travel factors are distractors and which factors are enhancers of passenger satisfaction. Building on Herzberg's two-factor motivation theory, this study aims to explore most frequently mentioned attributes of airport service quality and distinguish key drivers for passenger satisfaction/dissatisfaction in the airport context.

A content analysis of 1,095 traveler comments posted between 2010 and 2013 on an airport review web site was performed in order to identify satisfiers/dissatisfiers. The web spider randomly selected consumer comments related to 33 popular destinations.

The study results indicated key satisfiers in the airport context such as cleanliness and pleasant environment to spend time in. On the other side, security-check, confusing signage and poor dining offer are recognized as major dissatisfiers in the airport setting.

The study findings provide insight on predominant satisfiers, dissastisfiers and performance factors of airport service quality from passengers' perspectives. Airport management teams may use the study results to renovate airport facility and improve service quality.

To the best of the authors' knowledge, this study is the first to utilize the visual data mining techniques in examining airport users' experience. Visualization produced summaries of qualitative comments in the form of tag clouds, word networks, and word tree images that help discover the most emerging themes of travelers' complaints and compliments.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

The growth of the Chinese economy has resulted in a significant increase in construction and demolition waste (CDW), and regional differences in CDW generation are gradually increasing. The purpose of this study is to investigate the regional differences in CDW generation and the driving factors that influence CDW generation in different areas of China. To provide a systematic advisement for local governments to select the appropriate policy, reduce CDW generation.

The generation of CDW was calculated by region, based on the area estimation method, from 2005 to 2018. The relationship between CDW generation and economic development, and the driving factors of CDW generation in different regions of China, was investigated using the environmental Kuznets curve (EKC) model and the STIRPAT theoretical model.

CDW generation of China increased at the average annual growth rate of 10.86% from 2005 to 2018. The main areas of CDW generation were concentrated in the eastern and central regions, while the proportion of CDW generation in the northeast region decreased gradually, and the changes varied significantly across different regions. The EKC between CDW generation and economic development was established for the whole country, North China, Northeast China, East China, Central South China, Southwest China and Northwest China. Three main factors based on the STIRPAT theoretical model were identified and explained into a framework to reduce CDW generation. The results provided a useful theoretical basis and data support guide for devising effective policies and regulations for the Chinese context.

The findings from this study can ultimately support policymakers and waste managers in formulating effective policies for waste management strategies and CDW-specific legislation. Additionally, it can help the coordinated reduction of CDW generation across regions in China and can support construction enterprises (in their development strategies), similar developing economies and foreign firms planning to operate in China.

This study contributes to the field through the STIRPAT model on driving factors of CDW generation in the Chinese context, in different regions.