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The purpose of this paper is an investigation of driving behaviour and impacts on emissions at two traffic junctions.

A signalised junction and a roundabout in Edinburgh have been selected. An instrumented car has been used and a GPS to monitor driving activities as well as a gas analyser to monitor the vehicle's emissions during the evening peak hour.

Vehicles’ emissions are affected by a large number of factors including characteristics of the engine and the vehicle, characteristics of the road, the fuel used and driving behaviour.

Different methods and approaches have been used to investigate the behaviour of vehicles at various traffic junctions. The main aim, however, has mostly been to reduce travel times as well as traffic delays and queues at the junction. Consideration of environmental impacts has also been made, but often as a by‐product of congestion reduction and not as a main aim.

Early studies projected potential societal, economic and environmental benefits by the widespread deployment of Autonomous and Connected Transport (ACT) promising a significant reduction of transport costs and improvement in road safety. An effective way of assessing ACT impact is via simulations, where results are largely affected by the scenarios defining the ACT development. However, modelled scenarios are very diverse due to the huge uncertainty in ACT development and deployment. This chapter aims to shed light on the different ACT simulation scenarios and sustainability aspects that should be considered while developing or reporting the simulation results. To this end, this chapter discusses the various simulation approaches, what the required (or the typically utilised) pipelines are, and how some components are more important or less important than in ‘classic’ modelling and simulation approaches. Special focus is dedicated to the uncertainty related to ACT operational parameters and how these will impact transport modelling. To address said uncertainty, an analysis of current approaches to scenario building is provided, as the chapter guides the reader through different methodologies and clusters them in relation to the desired indicators. Finally, the chapter identifies and proposes Key Performance Indicators (KPIs) that are useful when applying simulation tools to assess ACT scenarios. These KPIs can be used for simulation scenario development to test particular sustainability aspects of ACT deployment and relevant policies.

Deregulation of domestic markets and the liberalization of international markets have dramatically changed air transportation. One of the important results of this change is the environmental effects of air transportation. This study aims to examine the implications of air transportation on environmental sustainability in the context of airline business strategies in liberalized and globalized air transport industry.

The paper discusses the relationship between liberalization, airline strategies and environmental sustainability of air transportation using the related literature. Then, to show some environmental impacts on the axis of the relationship discussed, emission rates for the aircraft landing and take-off phase were calculated on a global basis based on the aircraft traffic.

The discussion in the paper shows that the liberalization policies and the strategies of airlines supported by these policies, in essence, contradict the environmental sustainability of air transport. Considering the flight share projections of EUROCONTROL for different aircraft types on a global basis and the World Bank’s global flight traffic forecast for the years 2016 and 2025, it has been demonstrated that the number of aircraft departures will increase by 30%, whilst the number of aircraft emissions will increase by 41.5%.

Airlines are one of the main actors that will play a role in reducing the environmental impacts of air transportation. Therefore, this study is important in giving an idea to both policymakers and airline managers on how airline companies’ strategies should be shaped to realize both corporate sustainability and environmentally sustainable air transportation.

There are many studies in the literature regarding the environmental effects of air transport. However, there are not many studies linking environmental impacts with airline strategies that directly affect air transport demand. This study is different in that it gives environmental sustainability by associating it with its root causes.

The objective of this research work is to design a data-based solution for administering traffic organization in a smart city by using the machine learning algorithm.

A machine learning framework for managing traffic infrastructure and air pollution in urban centers relies on a predictive analytics model. The model makes use of transportation data to predict traffic patterns based on the information gathered from numerous sources within the city. It can be promoted for strategic planning determination. The data features volume and calendar variables, including hours of the day, week and month. These variables are leveraged to identify time series-based seasonal patterns in the data. To achieve accurate traffic volume forecasting, the long short-term memory (LSTM) method is recommended.

The study has produced a model that is appropriate for the transportation sector in the city and other innovative urban applications. The findings indicate that the implementation of smart transportation systems enhances transportation and has a positive impact on air quality. The study's results are explored and connected to practical applications in the areas of air pollution control and smart transportation.

The present paper has created the machine learning framework for the transportation sector of smart cities that achieves a reasonable level of accuracy. Additionally, the paper examines the effects of smart transportation on both the environment and supply chain.

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

This research examines factors that determine the improvement of the Russian supply chain sustainability. The strategic business model incorporates ecological, social and economic aspects.

Considering Trans-Siberian Railway as a typical case, the study selected several cases or the parts of the primary rail connection with the affiliation of important neighbouring countries. The study uses quantitative analyses of a variety of size parameters (e.g. volumes of traffic, logistics costs, delivery distance and air pollutants).

The empirical findings stress that supply chains should favour in the future railway (or intermodal) connections for piggyback and containerised cargo. Herein lays the reason for the examination of all traditional factors affecting the modal choice and their complementation by the parameters to measure sustainability throughout the supply chains. The inclusion of the green practices positively affected the environmental, social and economic performance of the new approach.

This research focuses on the delivery of cargo in containers and semi-trailers within wagons through the overland corridors. Despite the restrictive empirical findings within the national transport system, some elements can be representative of the international supply chains, provided that intermodal services are the most appropriate for the transportation over long distances.

Clients, media and regulatory bodies stress the consideration of environmental aspects at all stages of a global supply chain. Therefore, their adoption into strategic imperatives of local supply chains becomes inevitable.

An assessment of supply chains for longer distance transportation in Russia has not taken sustainability into account within cost analyses.

In the face of escalating urban populations, the quest for seamless mobility in cities becomes increasingly complex, even in regions where transit options are presumably accessible within the developing world. The imperative to confront urban mobility challenges and forge sustainable cities equipped with adept transportation and traffic management systems cannot be overstated. This study delves into the technological paradigms employed by developed nations and evaluates their pertinence in the current milieu for mitigating urban mobility challenges. Simultaneously, it scrutinizes the deployment of smart city technologies (SCTs) within developing nations, investigating potential technological strides that can be harnessed to achieve sustainable urban transportation. By dissecting the intricacies of SCTs in developing countries, the study aims to unearth viable technological advancements that can be judiciously implemented to foster sustainable urban mobility. It aspires to provide nuanced recommendations for the integration of latent SCTs, unlocking untapped potential to augment the sustainability of urban transportation in the developing world. The research also elucidates strategies geared towards fostering international collaborations which are instrumental in propelling the development of cities characterized by equity and inclusivity. The study underscores the significance of a global alliance in overcoming urban challenges, emphasizing the need for shared knowledge, resources and experiences to propel the evolution of cities towards a more sustainable and equitable future. This research serves as a comprehensive exploration of the intricate interplay between technology, urbanization and international cooperation, offering insights and recommendations pivotal to steering the trajectory of urban development in developing nations.

This study aims to examine the factors that influence hotel/motel employees’ helping behavior toward the victims of human trafficking.

Using a survey-based quantitative method, this study examines and compares two models of helping behavior based on egoism and altruism theories to measure the helping tendencies of lodging employees toward victims of human trafficking.

The study results show that perceived intrinsic rewards of helping and empathy with the victims are the major antecedents of employees’ likelihood to help the victims.

The study contributed to the egoism school of thought and the Cost-Reward Model by showing that only perceived intrinsic rewards drive individuals’ intention to help in risky covert situations, such as human trafficking, while perceived extrinsic rewards may demotivate people to help in these situations.

Previous studies overlooked the role of the lodging industry in human trafficking. This study focuses on service employees as potential helpers of the victims as they notice in hotels/motels.

Resilience concepts in integrated urban transport refer to the performance of dealing with external shock and the ability to continue to provide transportation services of all modes. A robust transportation resilience is a goal in pursuing transportation sustainability. Under this specified context, while before the perturbations, robustness refers to the degree of the system’s capability of functioning according to its design specifications on integrated modes and routes, redundancy is the degree of duplication of traffic routes and alternative modes to maintain persistency of service in case of perturbations. While after the perturbations, resourcefulness refers to the capacity to identify operational problems in the system, prioritize interventions and mobilize necessary material/ human resources to recover all the routes and modes, rapidity is the speed of complete recovery of all modes and traffic routes in the urban area. These “4R” are the most critical components of urban integrated resilience.

The trends of transportation resilience's connotation, metrics and strategies are summarized from the literature. A framework is introduced on both qualitative characteristics and quantitative metrics of transportation resilience. Using both model-based and mode-free methodologies that measure resilience in attributes, topology and system performance provides a benchmark for evaluating the mechanism of resilience changes during the perturbation. Correspondingly, different pre-perturbation and post-perturbation strategies for enhancing resilience under multi-mode scenarios are reviewed and summarized.

Cyber-physic transportation system (CPS) is a more targeted solution to resilience issues in transportation. A well-designed CPS can be applied to improve transport resilience facing different perturbations. The CPS ensures the independence and integrity of every child element within each functional zone while reacting rapidly.

This paper provides a more comprehensive understanding of transportation resilience in terms of integrated urban transport. The fundamental characteristics and strategies for resilience are summarized and elaborated. As little research has shed light on the resilience concepts in integrated urban transport, the findings from this paper point out the development trend of a resilient transportation system for digital and data-driven management.