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This study aims to contribute to the supply chain management (SCM) literature differently. It offers insightful information about the main enablers that affect supply chain efficacy (SCE). Therefore, this study examines the significant roles and the relationships between SC absorptive capacity, SC risk mitigation, supply chain agility (SCA) and supply chain integration (SCI) among manufacturing firms (MFs) in the Middle East region.

This paper performed a quantitative survey-based study to analyze the substantial roles of SC absorptive capacity, SC risk mitigation, SCA and SCI on SCE. Thus, the authors conducted an online survey through 260 MFs that are listed in the Chamber of the industries of Jordan, Egypt and Turkey that only responded by email. The main respondents were chief executive managers, operations managers, managers and logistics employees from both mid and top levels. The conceptual model was tested by using a hypothesis-testing deductive approach. The findings are based on covariance-based analysis and structural equation modeling (SEM) using partial least squares (PLS)-SEM software.

The PLS-SEM clearly shows a significant relationship between SC absorptive capacity, SCA and SCI on SCE, while surprisingly still, SC risk mitigation does not significantly affect SCE. Further, the outcomes of this study indicate that there is a significant effect of SCA as a mediating factor in the relationship between SC absorptive capacity and SCE directly and indirectly, as well as a moderating effect of SCI in the relation, whereas there is a nonsignificant effect by SC risk mitigation. Finally, there is a significant effect of SCI in the relationship between SC absorptive capacity and SC risk mitigation on SCE as a moderating factor.

This study introduces a theoretical insight and empirically presents that both SCA and SCI are proper logistics characteristics for mediating and moderating the impact of SC absorptive capacity on SCE. Such findings of this study can provide insightful implications for managers at different levels in MFs, stakeholders and policymakers regarding the importance of using the three mentioned enablers on SCE in MFs, in the Middle East firms, in particular, and in developing countries, in general.

In the context of the negotiations for apportionment of emission reduction post‐Kyoto regime, issues of equity and fairness have emerged. The purpose of this paper is to generate a model for equitable emission reduction apportionment.

The mathematical model has been designed utilizing mitigation capacity (based on gross domestic product (GDP)) and cumulative excess emissions as the criteria for apportionment. Quantitative results have been arrived at, using cumulative γ and parabolic mitigation emission reduction trajectories to demonstrate the impact on stakeholders.

The apportionment outcomes are independent of the specific trajectory fine‐tuned in the feasibility region. Since the apportionment takes into account entitlements and the mitigation capacity, Africa and India have negligible reduction targets in tune with the development goals in these economies. Substantial reduction commitments would fall on the USA and the EU countries. China gets a moderate target due to higher emissions and GDP.

The approach is in consonance with the principle of common but differentiated responsibility enunciated in the UNFCCC and the Kyoto Protocol. The method can easily incorporate emissions trading. The issue of population as a driving factor of emissions has been partially accounted for by considering the entire national GDP as an emission reduction responsibility factor, without considering population based GDP entitlements.

The generalized framework can be extended to situations involving responsibility apportionment in public policies dealing with externalities. The framework is original and will be useful to policymakers and other stakeholders dealing with climate change, as well as researchers looking at externalities of a global or national dimension.

A sample of capital trials in North Carolina was analyzed to determine the impact on death sentencing of introducing mitigators related to diminished capacity on behalf of defendants. The results show that mitigators of this type were frequently submitted to the jury for consideration, and if accepted, the chances of a defendant being sentenced to death were diminished. However, when these mitigators were submitted but not accepted, the defendant's likelihood of receiving a death sentence was substantially escalated. These findings suggest a need for attorneys to carefully weigh the advantages and disadvantages of presenting diminished capacity mitigators in capital trials, and if choosing to do so, the absolute necessity of convincing the jury of their validity.

Polyurea is an elastomeric two-phase co-polymer consisting of nanometer-sized discrete hard (i.e. high glass transition temperature) domains distributed randomly within a soft (i.e. low glass transition temperature) matrix. A number of experimental investigations reported in the open literature clearly demonstrated that the use of polyurea external coatings and/or internal linings can significantly increase blast survivability and ballistic penetration resistance of target structures, such as vehicles, buildings and field/laboratory test-plates. When designing blast/ballistic-threat survivable polyurea-coated structures, advanced computational methods and tools are being increasingly utilized. A critical aspect of this computational approach is the availability of physically based, high-fidelity polyurea material models. The paper aims to discuss these issues.

In the present work, an attempt is made to develop a material model for polyurea which will include the effects of soft-matrix chain-segment molecular weight and the extent and morphology of hard-domain nano-segregation. Since these aspects of polyurea microstructure can be controlled through the selection of polyurea chemistry and synthesis conditions, and the present material model enables the prediction of polyurea blast-mitigation capacity and ballistic resistance, the model offers the potential for the “material-by-design” approach.

The model is validated by comparing its predictions with the corresponding experimental data.

The work clearly demonstrated that, in order to maximize shock-mitigation effects offered by polyurea, chemistry and processing/synthesis route of this material should be optimized.

The purpose of this paper is to assess the extent to which adaptation projects have incorporated ecosystem services, as well as their redesigning options. The projects selected are listed under National Adaptation Programme of Action in West African region.

A desktop survey approach was used to review 168 projects from 13 countries across West Africa. The projects were categorized and analyzed according to their adaptation goal, thematic focus, their implementation duration and level of investment.

The adaptation initiatives are dominated by actions in the agricultural sector accounting for 32 per cent of the total. Further, they were characterized by small grants consideration with 63 per cent falling under US$1m budget, short-term implementation duration with 46 per cent having three years’ execution period. A large portion of projects (55 per cent) mentioned directly one or more ecosystem services, with provisioning services being referred to in 50 per cent of the cases.

Adaptation projects with ecosystem services components are more sustainable and beneficial to the community. Hence, more consideration of nature benefits during project design, more financial consideration and localizing of the projects to realize the global adaptation goal should be considered.

The purpose of this paper was to develop an integrated framework for assessing the flood risk and climate adaptation capacity of an urban area and its critical infrastructures to help address flood risk management issues and identify climate adaptation strategies.

Using the January 2011 flood in the core suburbs of Brisbane City, Queensland, Australia, various spatial analytical tools (i.e. digital elevation modeling and urban morphological characterization with 3D analysis, spatial analysis with fuzzy logic, proximity analysis, line statistics, quadrat analysis, collect events analysis, spatial autocorrelation techniques with global Moran’s I and local Moran’s I, inverse distance weight method, and hot spot analysis) were implemented to transform and standardize hazard, vulnerability, and exposure indicating variables. The issue on the sufficiency of indicating variables was addressed using the topological cluster analysis of a two-dimension self-organizing neural network (SONN) structured with 100 neurons and trained by 200 epochs. Furthermore, the suitability of flood risk modeling was addressed by aggregating the indicating variables with weighted overlay and modified fuzzy gamma overlay operations using the Bayesian joint conditional probability weights. Variable weights were assigned to address the limitations of normative (equal weights) and deductive (expert judgment) approaches. Applying geographic information system (GIS) and appropriate equations, the flood risk and climate adaptation capacity indices of the study area were calculated and corresponding maps were generated.

The analyses showed that on the average, 36 (approximately 813 ha) and 14 per cent (approximately 316 ha) of the study area were exposed to very high flood risk and low adaptation capacity, respectively. In total, 93 per cent of the study area revealed negative adaptation capacity metrics (i.e. minimum of −23 to <0), which implies that the socio-economic resources in the area are not enough to increase climate resilience of the urban community (i.e. Brisbane City) and its critical infrastructures.

While the framework in this study was obtained through a robust approach, the following are the research limitations and recommended for further examination: analyzing and incorporating the impacts of economic growth; population growth; technological advancement; climate and environmental disturbances; and climate change; and applying the framework in assessing the risks to natural environments such as in agricultural areas, forest protection and production areas, biodiversity conservation areas, natural heritage sites, watersheds or river basins, parks and recreation areas, coastal regions, etc.

This study provides a tool for high level analyses and identifies adaptation strategies to enable urban communities and critical infrastructure industries to better prepare and mitigate future flood events. The disaster risk reduction measures and climate adaptation strategies to increase urban community and critical infrastructure resilience were identified in this study. These include mitigation on areas of low flood risk or very high climate adaptation capacity; mitigation to preparedness on areas of moderate flood risk and high climate adaptation capacity; mitigation to response on areas of high flood risk and moderate climate adaptation capacity; and mitigation to recovery on areas of very high flood risk and low climate adaptation capacity. The implications of integrating disaster risk reduction and climate adaptation strategies were further examined.

The newly developed spatially explicit analytical technique, identified in this study as the Flood Risk-Adaptation Capacity Index-Adaptation Strategies (FRACIAS) Linkage/Integrated Model, allows the integration of flood risk and climate adaptation assessments which had been treated separately in the past. By applying the FRACIAS linkage/integrated model in the context of flood risk and climate adaptation capacity assessments, the authors established a framework for enhancing measures and adaptation strategies to increase urban community and critical infrastructure resilience to flood risk and climate-related events.

This study tries to examine how supply chain (SC) absorptive capacity (AC), SC ambidexterity, SC risk mitigation and supply chain agility (SCA) affect SC efficacy (SCE) in manufacturing firms (MFs) in the Middle East region.

Using a quantitative approach through a survey-based study, 1,004 questionnaires were distributed to the MFs that are listed in the chambers of the industries of Jordan, Egypt, Saudi Arabia and Bahrain in the Middle East region, with 239 useable and valid responses retrieved for analysis, representing a 23.8% response rate. The main respondents were chief executive managers, operations managers, managers and logistics managers from both mid and top levels. The conceptual model was tested by using a hypothesis-testing deductive approach. The findings are based on covariance-based analysis and structural equation modeling (SEM) using partial least squares-SEM (PLS-SEM) software.

This study illustrates a significant relationship between SC AC, SC ambidexterity, SC risk mitigation and SCA on SCE. Further, the findings indicate that there is a significant effect of SC risk mitigation as a mediating factor in the relationship between SC AC, and SC ambidexterity on SCE directly and indirectly, as well through a moderating effect of SCA in these relations. Finally, there is a significant direct and indirect effect of SCA in the relationship between SC AC and SC ambidexterity on SCE as a moderating factor.

This study presents theoretical and empirical insights that both SC risk mitigation and SCA are proper logistics features for mediating and moderating extends the literature by adding a positive role of SC AC and SC ambidextrousness in mitigating SC risks. However, this study adds up the SC literature by evidencing moderating role of SCA between the absorptive capacities, ambidexterity on SCE. Such findings of this study can provide insightful implications for managers and practitioners at different levels in and efficacy among MFs (MFs, stakeholders and policymakers regarding the importance of using the three mentioned enablers on SCE) in MFs, particularly in the Middle Eastern firms and in developing countries in general East region.

This chapter explores the reciprocal dynamics between climate change and tourism, underlining the imperative to comprehend this connection for effective mitigation strategies and sustainable practices. It focuses on two contrasting regions, the Mediterranean and Himalayan, elucidating their geographical and economic disparities. The Mediterranean, known for its coastal and marine attractions, faces high vulnerability to climate change, impacting outdoor recreation and tourism activities. This region experiences a Mediterranean climate characterised by distinct seasonal patterns, but it also grapples with high-impact atmospheric events like floods and droughts, while the Himalayan region is experiencing more untimely rain and snowfall, erratic monsoons, and decreased snowfall. These climatic challenges, coupled with a growing population and dependence on imported resources, necessitate adaptation strategies for the agricultural and food production sectors. This chapter evaluates climate anomalies and impacts in both the Indian Himalayan and the Adriatic region, with a particular focus on the tourism industry’s adaptation and mitigation capacities.

In addition to vulnerabilities resulting from climate change, it also analysed existing measures and documents related to climate change, as well as their effectiveness based on the expert opinion of the focus groups. The findings reveal that both regions experience shared and region-specific climate change impacts, affecting agriculture, water resources, human health, and infrastructure. Further research opportunities are identified, including the study of ecosystem resilience, biodiversity preservation, sustainable water resource management, and long-term public health implications of changing climatic conditions. This chapter underscores the urgency of climate action and the imperative for adaptive strategies in a complex and uncertain landscape.

This study aims to investigate the feasibility of employing a multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation. The formulated objectives are the minimisation of the total allocation cost of the anti-fraud capacities and the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots.

From the literature survey conducted and primary qualitative data gathered from the 17 licenced banks in South Africa on fraud investigators, the suggested fraud investigators are the organisation’s finance department, the internal audit committee, the external risk manager, accountants and forensic accountants. These five human resource capacities were considered for the formulation of the multi-objectives integer programming (MOIP) model. The MOIP model is employed for the optimisation of the employed capacities for cyberfraud mitigation to ensure the effective allocation and utilisation of human resources. Thus, the MOIP model is validated by a genetic algorithm (GA) solver to obtain the Pareto-optimum solution without the violation of the identified constraints.

The formulated objective functions are optimised simultaneously. The Pareto front for the two objectives of the MOIP model comprises the set of optimal solutions, which are not dominated by any other feasible solution. These are the feasible choices, which indicate the suitability of the MOIP to achieve the set objectives.

The results obtained indicate the feasibility of simultaneously achieving the minimisation of the total allocation cost of the anti-fraud capacities, or the maximisation of the forensic accounting capacities in all cyberfraud incident prone spots – or the trade-off between them, if they cannot be reached simultaneously. This study recommends the use of an iterative MOIP framework for decision-makers which may aid decision-making with respect to the allocation and utilisation of human resources.

The originality of this work lies in the development of multi-objectives integer-programming model for effective allocation of resources for cyberfraud mitigation.

This paper aims to examine the policy environments, institutional arrangements and practical implementation of some initiatives undertaken by the Government of Cameroon, together with some relevant stakeholders, in addressing climate change mitigation and adaptation at various levels in the country, which are prerequisites to promote synergistic ways of addressing climate change mitigation and adaptation.

Using a qualitative approach to data collection, the paper draws upon information collected from relevant literature and interviews with 18 key country resource personnel.

Results revealed that most reviewed policies/programs/strategies do not mention “climate change” explicitly but propose some activities which indirectly address it. Interaction is fair within the government ministries but weak between these ministries and other institutions. Inadequate financial resources are being opined as the most important challenge stakeholders are (and would continue) facing as a result of adopting integrated approaches to climate change. Other challenges include inadequate coordination, insufficient sensitization and capacity building, ineffective implementation, inadequate compliance, lack of proper transparency and inadequate public participation. To redress the aforementioned constraints and challenges, the paper concludes by outlining a number of recommendations for policy design.

The following recommendations were made: create a national technical committee to oversee and provide scientific guidance to the government on synergistic approaches; promote private sector investment and sponsorship on synergistic approaches; create local awareness, etc. It is important to underscore that minimal studies have been conducted to analyze multi-stakeholder perspectives on synergies between climate change mitigation and adaptation in Cameroon. This study attempts to bridge this major gap.