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Food manufacturing supply chain systems are the most relevant wheels of the world economy since they provide essential products supporting daily life. Nevertheless, various supply inefficiencies have been reported to compromise food safety in different regions. Sustainable supplier management and digitalization practices have become cornerstone activities in addressing these shortcomings. Therefore, this paper proposes an integrated method for sustainability management in digital manufacturing supply chain systems (DMSCS) from the food industry.

The Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) was used to weigh the criteria and subcriteria under uncertainty. Second, the Intuitionistic Fuzzy Decision-Making Trial and Evaluation Laboratory (IF-DEMATEL) was applied to determine the main DMSCS sustainability drivers whilst incorporating the expert's hesitancy. Finally, the Combined Compromise Solution (CoCoSo) was implemented to pinpoint the weaknesses hindering DMSCS sustainability. A case study from the pork supply chain was presented to validate this method.

The most important criterion for DMSCS sustainability management is “location” while “manufacturing capacity” is the most significant dispatcher.

This paper presents a novel approach integrating IF-AHP, IF-DEMATEL, and CoCoSo methods for sustainability management of DMSCS pillaring the food industry.

The process of predicting construction costs and forecasting price fluctuations is a significant and challenging undertaking for project managers. This study aims to develop a construction cost index (CCI) for Jordan’s construction industry using fuzzy analytic hierarchy process (FAHP) and predict future CCI values using traditional and machine learning (ML) techniques.

The most influential cost items were selected by conducting a literature review and confirmatory expert interviews. The cost items’ weights were calculated using FAHP to develop the CCI formula.

The results showed that the random forest model had the lowest mean absolute percentage error (MAPE) of 1.09%, followed by Extreme Gradient Boosting and K-nearest neighbours with MAPEs of 1.41% and 1.46%, respectively.

The novelty of this study lies within the use of FAHP to address the ambiguity of the impact of various cost items on CCI. The developed CCI equation and ML models are expected to significantly benefit construction managers, investors and policymakers in making informed decisions by enhancing their understanding of cost trends in the construction industry.

Considering the human factor, the quality of the personnel is vital to ensure especially the value creation in the ports. Therefore, employee quality stands out for withstanding the pressures that stem from global trade on its operational speed felt by ports in recent years. Accordingly, the selection of the qualified personnel at the ports is very critical and a tool based on dynamic capabilities is needed to manage this process well. The aim of this study is to develop a model based on dynamic capabilities for recruitment process of ports.

Port personnel should have dynamic capabilities detected from the literature. These capabilities were approached as criteria. In this study, Buckley's proposed fuzzy analytical hierarchy process (AHP) method was employed for weighting the whole criteria. After that, weights of the criteria were used to prioritize alternatives with the fuzzy TOPSIS method.

This model reflects port managers' priorities and port customers' evaluations. Thus, the model can also reflect the level of integration of ports' related department managers into the recruitment process. The analyses allow the evaluation of the attitudes of the human resources department in the related port while fulfilling the personnel recruitment function. As a result of analyses, differences between perceptions of port managers and customers served as a feedback to the human resource management department of the ports.

One of the originalities of this study was derived from its customer-oriented perspective. This is a unique study that gathers common personnel capabilities related to the operation, planning and customer relationship departments and evaluates the success of these capabilities from the customer perspective.

This study aims to conduct the aircraft electrical wiring interconnection system (EWIS) safety risk assessment process abundantly and hierarchically and establish the assessment index system considering the weights and interrelationships of different levels of indices.

Due to the failure of EWIS being multifactorial, hidden and diverse, this paper divides the factors influencing the failure of EWIS into 3 primary indices, 13 secondary indices and 38 tertiary indices. Taking open circuit failure (OCF) and short circuit failure (SCF) as examples, calculate the weights of assessment indices based on the triangular fuzzy number analytic hierarchy process (TFNAHP) and triangular fuzzy number decision-making trial and evaluation laboratory (TFNDEMATEL). The cloud model (CM) divides the risk levels and obtains the safety risk assessment results. The comparative analyses of different weight calculation methods, different failure modes and different aircraft EWIS zones verify the effectiveness and practicability of the proposed method.

The results show that the proposed method aligns more with the actual situation than other methods. Also, the results identify key focus objects in EWIS safety risk assessment, such as the surrounding environmental factors among the primary indices having the most significant influence on OCF and SCF, the risk level of SCF being higher than that of OCF, etc.

This paper proposes a safety risk assessment index system for aircraft EWIS based on the cable parameters, surrounding environmental factors, installation and protection methods. The weight assignment is added to the assessment index system, and the safety risk assessment model is constructed by combining TFNAHP, TFNDEMATEL and CM.

This study aims to assess readiness for climate change mitigation in the Kingdom of Bahrain.

Two stages were followed aiming at understanding the situation related to climate change mitigation in Bahrain and assessing the mitigation readiness. Baseline and mitigation scenarios for the period 2019–2040 were developed using the Low Emissions Analysis Platform software based on historical emissions and energy data for the period 1990–2018. Using the analytic hierarchy process, the mitigation readiness was assessed by 13 experts, and priority areas for mitigation action were identified.

CO₂e emissions are projected to grow continuously. However, no explicit climate change strategy is in place yet. Mitigation is tackled implicitly through energy efficiency and renewable energy initiatives. These initiatives can make 23% reduction in CO₂e emissions by 2040. Adopting additional measures is needed to achieve the recently set emission reduction target of 30% by 2035. The findings revealed potential areas for improving mitigation efforts in Bahrain. Priority areas for mitigation actions, as identified by experts, were mainly related to policy and governance. Focus needs to be paid to the social aspect of climate change mitigation.

Literature on mitigation readiness in developing countries is sparse. Knowledge of the requirements for climate change mitigation and assessment of the country’s performance can prioritize areas for improving mitigation action. Several lessons can be learnt from the case of Bahrain. In addition, the adopted methodology can be applied to other developing or Arab countries at local or institutional levels. However, its application to specific sectors may require adjustments.

Reportedly, green roof (GR) makes a significant contribution towards a truly sustainable-built environment; however, its implementation is yet to hit a sufficient level in developing countries. Thus, this study assesses GR implementation strategies in developing countries by providing a comparative analysis through experts in Kazakhstan, Malaysia and Turkey.

The study adopts a four-step methodological approach to achieve the research aim: literature review, focus group discussion, fuzzy analytical hierarchy process (FAHP) analysis and correlation analyses. First, a literature review followed by a focus group discussion is used to determine 18 (out of 25 initially) strategies for the selected context and these are classified into three categories: governmental and institutional support, knowledge and information and policy and regulation. Afterward, the identified GR strategies are evaluated using the FAHP with the data gathered from the experts in the countries studied. Finally, correlation analyses were used to observe the strength of agreement between the assessments of experts from the included countries.

The findings indicate that financial incentives, low-cost government loans and subsidies and tax rebates are the essential strategies for the wider adoption of GR. Evaluating the policy and regulations strategies also showed that mandatory GR policies and regulations and better enforcement of the developed GR policies are ranked as the most prominent strategies. The findings show a low level of agreement among respondents from Kazakhstan, while there is a high level of agreement between the experts in Malaysia and Turkey.

The research contribution is twofold. First (research implication), the study identifies the strategies through a complete literature review. Second, the identified strategies are evaluated through the lenses of experts in three developing countries which are hoped to provide (practical contribution) a better understanding of the most effective strategies that require attention and enable the frontline stakeholders (particularly government authorities) to focus on them.

The study findings provide a good point of departure to explore the strategies for broader adoption of GRs in developing economic setting.

The statistics show that older adults have been major fire victims in high-rise buildings. However, the fire safety building codes in most countries are not inclusive and do not reflect provisions for older adults. The research aims to develop a fire risk assessment index system for older adults living in high-rise residential buildings in India. The study further develops a fire rating system to improve fire safety provisions in high-rise buildings in India.

The paper employs Delphi, analytic hierarchy process (AHP) and fuzzy comprehensive risk evaluation techniques. It considers 18 in-depth interviews and group discussions with builders, developers, architects, policymakers, and fire safety experts and consultants to develop a fire risk assessment system for older occupants living in high-rise residential buildings in India.

The fire protection systems and fire management systems are not as per the needs of older adults. The egress system components need improvisation considering the challenges of older adults.

The study is limited to older adults living in high-rise residential buildings in the capital city of Gujarat, Ahmedabad.

This study will assist policymakers in developing fire safety standards that are targeted to the needs of older persons living in high-rise residential buildings during a fire evacuation.

While several approaches for measuring fire risk in high-rise residential buildings exist, no such system has been developed specifically for older adults in India.

Artificial intelligence (AI) is the most progressive commodity among current information system applications. In-house development and sales of beneficial products are difficult for many software development and service companies (SDSCs). SDSCs have some implicit concerns about implementing AI software development due to the complexity of AI technology; they require an evaluation framework to avoid development failure. To fill the void, this study identified the factors influencing SDSCs when developing AI software development.

Based on complex adaptive systems theory, three aspects were developed as the main factors of hierarchy, namely, employees' capabilities, environmental resources and team capabilities. Fuzzy analytic hierarchy process (FAHP) was used to assess the SDSCs' attitude. Based on SDSCs, attitudes toward implementing AI software projects were collected to calculate the hierarchy of factors.

The outcome of FAHP is used as understanding the key factors of SDSCs for selecting an AI software project, toward the improvement of overall project planning. Employees' stress resistance was considered as a priority for the project, although professional AI skills and resources were also important.

This study suggested three variables developed using complex adaptive systems. This study contributes to a better understanding of the critical aspects of developing AI software projects in SDSCs. The study's findings have practical and academic implications for SDSCs and subsequent academic development, broadening the scope of AI software development research.

Unforeseen events can disrupt the operational process and negatively impact emergency resources optimization and its supply chain. A limited number of studies have addressed risk management issues in the context of emergency supply chains, and this existing research lacks inbuilt and practical techniques that can significantly affect the reliability of risk management outcomes. Therefore, this paper aims to identify and practically analyze the specific risk factors that can most likely disrupt the normal functioning of the emergency supply chain in disaster relief operations.

This paper has used a three-step process to investigate and evaluate risk factors associated with the emergency supply chain. First, the study conducts a comprehensive literature review to identify the risk factors. Second, the research develops a questionnaire survey to validate and classify the identified risk factors. At the end of this step, the study develops a hierarchical structure. Finally, the research investigates the weighted priority of the validated risk factors using the fuzzy-analytical hierarchy process (FAHP) methodology. Experts were required to provide subjective judgments.

This paper identified and validated 28 specific risk factors prevalent in emergency supply chains. Based on their contextual meanings, the research classified these risk factors into two main categories: internal and external risk factors; four subcategories: demand, supply, infrastructural and environmental risk factors; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social and political risk factors. The most significant risk factors include war and terrorism, the absence of legislative rules that can influence and support disaster relief operations, the impact of cascading disasters, limited quality of relief supplies and sanctions and constraints that can hinder stakeholder collaboration. Therefore, emergency supply chain managers should adopt appropriate strategies to mitigate these risk factors.

This study will contribute to the general knowledge of risk management in emergency supply chains. The identified risk factors and structural hierarchy taxonomic diagram will provide a comprehensive risk database for emergency supply chains.

The research findings will provide comprehensive and systemic support for respective practitioners and policymakers to obtain a firm understanding of the different risk categories and specific risk factors that can impede the effective functioning of the emergency supply chain during immediate disaster relief operations. Therefore, this will inform the need for the improvement of practices in critical aspects of the emergency supply chain through the selection of logistics and supply chain strategies that can ensure the robustness and resilience of the system.

This research uses empirical data to identify, categorize and validate risk factors in emergency supply chains. This study contributes to the theory of supply chain risk management. The study also adopts the fuzzy-AHP technique to evaluate and prioritize these risk factors to inform practitioners and policymakers of the most significant risk factors. Furthermore, this study serves as the first phase of managing risk in emergency supply chains since it motivates future studies to empirically identify, evaluate and select effective strategies that can eliminate or minimize the effects of these risk factors.

In the analysis of structures in a fire situation by simplified and analytical methods, one assumption is that the fire resistance time is greater than or equal to the required fire resistance time. Among the methodologies involving the fire resistance time, the most used is the tabular method, which associates fire resistance time values to structural elements based on minimum dimensions of the cross section. The tabular method is widely accepted by the technical-scientific community due to the fact that it is safe and practical. However, its main criticism is that it results in lower fire resistance times than advanced thermal and thermostructural analysis methods. The objective of this study was to evaluate the fire resistance time of reinforced concrete beams and compare it with the required fire resistance time recommended by the tabular method of NBR 15200 (ABNT, 2012).

The fire resistance time and required fire resistance time of reinforced concrete beams were evaluated using, respectively, numerical models developed based on the finite element method and the tabular method of NBR 15200 (ABNT, 2012). The influence of the following parameters was investigated: longitudinal reinforcement cover, characteristic compressive strength of concrete, beam height, longitudinal reinforcement area and arrangement of steel bars.

Among the evaluated parameters, the covering of the longitudinal reinforcement proved to be more relevant for the fire resistance time, justifying that the tabular method of NBR 15200 (ABNT, 2012) being strongly and directly influenced by this parameter. In turn, more resistant concretes, higher beams and higher steel grades have lower fire resistance time values. This is because beams in these conditions have greater resistance capacity at room temperature and, consequently, are subject to external stresses of greater magnitude. In some cases, the fire resistance time was even lower than the required fire resistance time prescribed by NBR 15200 (ABNT, 2012). Both the fire resistance time and the required fire resistance time were not influenced by the arrangement of the longitudinal reinforcements.

The present paper innovates by demonstrating the influence of other important design variables on the required fire resistance time of the NBR 15200 (ABNT, 2012). Among several conclusions, it was found that the load level to which the structural elements are subjected considerably affects their fire resistance time. For this reason, it was recommended that the methods for calculating the required fire resistance time consider the load level. In addition, the article quantifies the security degree of the tabular method and exposes some situations for which the tabular method proved to be unsafe. Moreover, in all the models analyzed, the relationship between the span and the vertical deflection associated with the failure of the beams in a fire situation was determined. With this, a span over average deflection relationship was presented in which beams in fire situations fail.