Advanced decision making in sustainable city logistics projects : criteria and, risk identification and assessment

Les villes sont les lieux de la plus grande concentration d'activités sociales et économiques. La logistique est l'une des plus importants éléments de la durabilité et de l'économie d’une la ville. Pour la logistique urbaine, il est nécessaire de prendre en compte les caractéristiques de la ville et les objectifs de toutes les parties prenantes (expéditeurs, destinataires, transporteurs, prestataires de services logistiques, résidents, gouvernement de la ville). Les plans de logistique urbaine durable pourraient avoir un impact significatif sur la qualité de la vie en milieu urbain. L'évaluation d'initiatives de logistique de ville durable (SCLI) telles que les centres de distribution urbains, la tarification de la congestion, le délai de livraison et les restrictions d'accès est un problème complexe, car plusieurs critères et contraintes subjectifs et objectifs doivent être pris en compte. Les administrations municipales investissent dans des initiatives de logistique urbaine durable telles que les centres de distribution urbains, la tarification de la congestion, le calendrier de livraison et les restrictions d'accès afin d'améliorer les conditions de transport de marchandises dans les villes et de réduire leurs impacts négatifs sur les citoyens et leur environnement. Cependant, il y a toujours des risques dynamiques associés à la sélection. L’analyse des risques des initiatives de logistique urbaine est une tâche complexe en raison de la multiplicité des facteurs de risque et de leurs dépendances. Bien qu'il n'y ait pas beaucoup d'études sur les risques liés à la logistique urbaine, aucune attention n'a été portée à l'analyse des risques liés à la logistique urbaine en prenant en compte les dépendances entre les facteurs de risque et leurs critères. Considérer les dépendances entre les facteurs de risque pourrait conduire à une analyse plus précise des risques et augmenter le taux de réussite de la sélection des initiatives de logistique urbaine. Méthodes: pour résoudre ce problème, nous proposons un outil avancé d'aide à la décision appelé «cartescognitives floues» (FCM), capable de gérer les risques associés à des systèmes aussi complexes. La FCM représente avec précision le comportement de systèmes complexes et peut prendre en compte les incertitudes, les informations imprécises, les interactions entre les facteurs de risque, la rareté de l'information et les opinions de plusieurs décideurs. En outre, il pourrait être appliqué à différents problèmes de prise de décision liés aux initiatives de logistique de ville durable (SCLI). Par conséquent, l'outil proposé aiderait les praticiens à gérer les risques liés à la logistique urbaine d'une manière plus efficace et proactive et offrirait de meilleures solutions d'atténuation des risques. Dans les études précédentes, les méthodes de décision multicritères étaient principalement utilisées pour l'évaluation, la comparaison et la sélection d'initiatives logistiques de villes en fonction des effets obtenus ou prévus résultant de leur introduction dans divers environnements urbains. Afin d'évaluer l'adéquation des solutions conceptuelles aux exigences des différentes parties prenantes et conformément aux attributs spécifiques de l'environnement urbain, il convient de définir des solutions conceptuelles associant différentes initiatives de logistique urbaine en utilisant un processus artificiel; outils de renseignement, y compris la FCM.The cities are the places of the largest concentration of social activities and economic. Logistics is one of the most important for the sustainability and the economy of the city. Inselecting the city logistics concept, it is necessary to consider the characteristics of the city and the goals of all the stakeholders (shippers, receivers, carriers, logistics service providers, residents, city government). Sustainable city logistics (SCL) plans could significantly affect the quality of life in the urban environment. Evaluating sustainable city logistics initiatives (SCLI) such as urban distribution centres, congestion pricing, delivery timing and access restrictions is a complex problem since several subjective and objective criteria and constraints should be considered. Municipal administrations are investing in sustainable city logistics initiatives (SCLI) such as urban distribution centres, congestion pricing, delivery timing and access restrictions in order to improve the condition of goods transport in cities and reduce their negative impacts on citizens and their environment. However, there is always some dynamic risks associated that should be selected. Risk analysis of sustainable city logistics initiatives is a complex task due to consisting of many risk factors with dependencies among them. Although there are no lots of studies on sustainable city logistics risks, no attention has been paid to the risk analysis of sustainable city logistics by considering the dependencies among risk factors and their criteria. Considering the dependencies among risk factors could lead to more precise risks analysis and increase the success rate of selecting sustainable city logistics initiatives. Methods: To address this, we are proposing an advanced decision support tool called "Fuzzy Cognitive Maps" (FCM) which can deal with risks of such complicated systems. FCM represents the behaviour of complex systems accurately and is able to consider uncertainties, imprecise information, the interactions between risk factors, information scarcity, and several decision maker's opinions. In addition, it could be applied to different decision makings problems related to sustainable city logistics initiatives (SCLI). Therefore, the proposed tool would help practitioners to manage sustainable city logistics risks in a more effective and proactive way and offer better risk mitigation solutions. In previous studies, multi-criteriadecision-making methods are mainly used for the evaluation, comparison and selection of individual sustainable city logistics initiatives in relation to the achieved or planned effects resulting from their introduction in various urban environments. In order to assess the suitability of the conceptual solutions to the requirements of different stakeholders, and in accordance with the specific attributes of the urban environment, there is the definition of conceptual solutions that combine different sustainable city logistics initiatives by using an artificial; intelligence tools including FCM

Forecasting project success in the construction industry using adaptive neuro-fuzzy inference system

Project managers often find it a challenge to successfully manage construction projects. As a result, understanding, evaluating, and achieving project success are critical for sponsors to control projects. In practice, determining key success factors and criteria to assess the performance of construction projects and forecast the success of new projects is difficult. To address these concerns, our objective is to go beyond the efficiency-oriented project success criteria by considering both efficiency- and effectiveness-oriented measures to evaluate project success. This paper contributes to existing knowledge by identifying a holistic and multidimensional set of project success factors and criteria using a two-round Delphi technique. We developed a decision support system using the Adaptive Neuro-Fuzzy Inference System (ANFIS) to forecast the success of mid- and large-sized construction projects. We gathered data from 142 project managers in Australia and New Zealand to implement the developed ANFIS. We then validated the constructed ANFIS using the K-fold cross-validation procedure and a real case study of a large construction project in Western Australia. The forecasting accuracy measures R2=0.97461, MAPE = 2.57912%, MAE = 1.88425, RMSE = 2.3610, RRMSE = 0.03149, and PI = 0.01589 suggest that the developed ANFIS is a very good predictor of project success

Deploying Process Innovation in Manufacturing

Manufacturing companies are increasingly under pressure to innovate due primarily to the intense competition they face, particularly under global market conditions. Innovation is recognised as a precondition for survival. Implementation of innovative initiatives in manufacturing is an important and challenging phase of process innovation. This is more so in the pre-implementation phase, in which manufacturing organisations need to prepare and be appropriately ready to deploy their process innovation initiative. This thesis focuses on the methodology of deploying process innovation in manufacturing to identify the factors influencing deployment readiness, evaluate hypothesised influences of some of the factors on deployment readiness, and provide an accessible method of assessing deployment readiness levels. Several important results and significant contributions to knowledge are arising from the research reported in this thesis. The thesis reports on the findings that several factors can influence deployment process innovation which is characterised along the dimensions of context for process innovation, performance, capability and capacity, resources, and collaboration. Through developing and evaluating a conceptual framework for process innovation deployment readiness, the thesis found a significant positive link between process innovation deployment preparedness and being fully ready to deploy. It was also found that having a deployment plan has a significant positive influence on being fully ready to deploy process innovation. These results have important implications for manufacturing managers, especially regarding the need for a deployment plan, ensuring a good climate for innovation, and being prepared to deploy process innovation in manufacturing. Perspectives of manufacturing managers reported in the thesis indicate that manufacturing companies do not necessarily need to attain a 100% deployment readiness level. On average, the companies appear satisfied with about 70% deployment readiness level. A fuzzy logic method for assessing manufacturing process innovation deployment readiness level presented in this thesis will help manufacturing companies gauge their readiness level and identify areas of improvement should they wish to increase their deployment readiness level prior to implementation. The method was validated in a case study company and found useful. The thesis concludes by reinforcing the need for manufacturing companies to rely more on appropriate techniques, such as those arising from this research, for use in successfully managing the deployment of their process innovation initiatives

Stream processing data decision model for higher environmental performance and resilience in sustainable logistics infrastructure

Purpose: As the global freight transport network has experienced high vulnerability and threats from both natural and man-made disasters, as a result, a huge amount of data is generated in freight transport system in form of continuous streams; it is becoming increasingly important to develop sustainable and resilient transport system to recover from any unforeseen circumstances quickly and efficiently. The aim of this paper is to develop a stream processing data driven decision-making model for higher environmental performance and resilience in sustainable logistics infrastructure by using fifteen dimensions with three interrelated domains. Design/methodology/approach: A causal and hierarchical stream processing data driven decision-making model to evaluate the impact of different attributes and their interrelationships and to measure the level of environmental performance and resilience capacity of sustainable logistics infrastructure are proposed. This work uses fuzzy cognitive maps (FCMs) and fuzzy analytic hierarchy process (FAHP) techniques. A real-life case under a disruptive event scenario is further conducted. Findings: The result shows which attributes have a greater impact on the level of environmental performance and resilience capacity in sustainable logistics infrastructure. Originality/value: In this paper, causal and hierarchical stream processing data decision and control system model was proposed by identified three domains and fifteen dimensions to assess the level of environmental performance and resilience in sustainable logistics infrastructure. The proposed model gives researchers and practitioners insights about sustainability trade-offs for a resilient and sustainable global transport supply chain system by enabling to model interdependencies among the decision attributes under a fuzzy environment and streaming data

Modeling the Critical Success Factors for BIM Implementation in Developing Countries: Sampling the Turkish AEC Industry

One of the latest advancements transforming the global architectural, engineering, and construction (AEC) industry is building information modeling (BIM). Although BIM implementation is at high level in developed countries, it is at a lower level in developing countries. BIM is new to the construction industry in Turkey, with only minor construction firms having implemented it. When making projections based on the current state of the Turkish AEC industry, it is foreseen that it will become mandatory in the near future. Considering this projection, it is doubtful that many construction companies will be caught unprepared for this situation and will not know how to implement BIM. Therefore, this study aimed to identify and model the critical success factors for BIM implementation and their impact size in order to gain insight for the fast and efficient implementation of BIM among construction firms in the Turkish AEC industry, which can be generalized for most developing countries. To reach these aims, a questionnaire was designed with 41 identified success criteria (SC) that were derived through a systematic literature review (SLR). The survey was conducted on construction professionals who actively implement BIM technology at their occupied firms in Turkey and they were asked to rank the importance of 41 SC on a five-point Likert scale. The sampling frame consisted of architects and civil engineers, and in total, 243 responses were received. The differentiation between SC and critical success criteria (CSC) was obtained by using a normalized mean cutoff value. An exploratory factor analysis (EFA) was used to identify the critical success factors (CSFs), and structural equation modeling (SEM) was used to examine the underlying size effects of each CSF on BIM implementation in the Turkish AEC industry. The results of this study reveal 20 CSC for successful BIM implementation, and EFA exhibited three CSFs from 20 CSC. Three critical success factors for BIM implementation in the Turkish construction industry were determined and grouped into two categories. “Awareness of technological benefits” and “organizational readiness and competitive advantages” formed one group and are the most influential critical success factors for BIM implementation. “Motivation of management regarding BIM” formed the second group of critical success factors that have a significant effect. © 2022 by the authors

Development of a lean principles framework for ERP implementation process

The aim of this research is to develop a novel framework based on lean principles and tools to be exploited in managing ERP implementation processes in order to enhance the overall success rate of the implementation project, which in turn minimises cost and time overruns. The framework consists of three stages built in a logical sequence taking into consideration the requirements of ERP projects implementations and the lean transformation principles. The first stage starts with an assessment model to measure the organisational readiness for implementing ERP system using leanness assessment approach. The second stage of the framework introduces the use of the Obeya lean tool along with a change management model to help visualize and streamlining the process of ERP implementation. In the final stage, a value stream mapping technique is used to identify potential waste occurrence and eliminate non-value adding activities from the process. As a result, a new eight stages ERP implementation process is developed and presented with descriptions on the activities encompassed in each stage. A research methodology consisting of four major phases was employed to attain the targeted objectives of the research; beginning with project initiation and contextual definition followed by data collection and field study. The data acquired from the previous two phases were used to conduct a thorough analysis from which key findings were drawn and used in the creative development of the readiness assessment model and the framework. Finally, elementary aspects of the framework were put to scrutiny through live case studies and professional expert judgement. The author made use of both qualitative and quantitative research measures. A validation for the ERP readiness assessment model is conducted initially on three case studies, and then the whole framework is validated through two other case studies and experts’ judgments. The results and overall feedback reflected a high level of acceptance of the framework structure and approach. The novel framework has the capability to improve the ERP implementation process providing it is utilised fully. It helps organisation to successfully deliver ERP systems on time, on budget, and with the required functionalities with high-level of acceptance from all stakeholders

Human Error in Commercial Fishing Vessel Accidents: An Investigation Using the Human Factors Analysis and Classification System

The commercial fishing industry is frequently described as one of the most hazardous occupations in the United States. The objective, to maximize the catch, is routinely challenged by a variety of elements due to the environment, the vessel, the crew, and several external considerations and how they interact with each other. The analysis of fishing vessel accidents can be complicated due to the diverse nature of the industry, including the species caught, the type and size of boat that is employed, how far travelled from their homeport, and the adequacy of the support organizations ensuring safe and uninterrupted operations. This study will develop and evaluate a version of Wiegmann and Shappell’s (2003) Human Factors Analysis and Classification System (HFACS), specifically for commercial fishing industry vessels (HFACS-FV), using ten years of data documenting the causes of fatal accidents in the commercial fishing industry. For this study, the accident investigation information will be converted into the HFACS-FV format by independent raters and measured for inter-rater reliability. The results will be analyzed for the frequency of the causal factors identified by the raters, and causal factors will also be evaluated for their relationship with vessel demographic information. Based on the results, the conclusion of the study will determine the efficacy of the HFACS-FV model

A decision-making framework for assessing the safety culture of maritime organizations with commercial cargo-carrying vessels

Maritime safety culture is currently one of the most important aspects of shipping. It enables maritime administrators to assess and manage safety-related issues proactively. However, most maritime organisations have not been able to effectively assess and manage safety-related issues proactively because of the challenges associated with the availability of safety performance data and the suitability of correlational statistical techniques used in safety culture assessments. Hence, researchers and professionals constantly debate which correlational statistical technique would be most suitable for assessing safety culture. This thesis aims to contribute to safety culture assessment from a methodological perspective of developing a decision-making framework for assessing maritime safety culture. Therefore, this PhD study offers an original contribution to knowledge regarding the application of decision-making techniques in a way that researchers have not previously done in assessing the safety culture of maritime organisations with commercial cargo-carrying vessels. Consequently, the integrated decision-making methodology adopted for this study entailed: the application of Analytical Hierarchy Process (AHP) in establishing weightage and priority setting of safety factors used in further assessments; the application of Simple Additive Weighting (SAW) in establishing the weighted safety climate performance of both shoreside staff and shipboard staff; the application of Pareto analysis in justifying the findings of the weighted safety climate and gaining insights into issues concerning occupational health and safety, ship safety, and shore-to-ship safety; and the application of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in scheduling vessels for safety culture improvement programs. The established weightage and priority setting of safety factors are: COMMUNICATION (COM) 0.15, EMPOWERMENT (EMP) 0.13, FEEDBACK (FDB) 0.11, MUTUAL TRUST (MTR) 0.11, PROBLEM IDENTIFICATION (PID) 0.13, PROMOTION OF SAFETY (POS) 0.12, RESPONSIVENESS (RSP) 0.11, and SAFETY AWARENESS (SAW) 0.14. Subsequently, the weighted safety climate performance of shoreside staff were: (COM) 0.651, EMPOWERMENT (EMP) 0.528, FEEDBACK (FDB) 0.418, MUTUAL TRUST (MTR) 0.365, PROBLEM IDENTIFICATION (PID) 0.543, PROMOTION OF SAFETY (POS) 0.451, RESPONSIVENESS (RSP) 0.448, and SAFETY AWARENESS (SAW) 0.515; while those of shipboard staff were: COMMUNICATION (COM) 0.570, EMPOWERMENT (EMP) 0.523, FEEDBACK (FDB) 0.432, MUTUAL TRUST (MTR) 0.419, PROBLEM IDENTIFICATION (PID) 0.517, PROMOTION OF SAFETY (POS) 0.458, RESPONSIVENESS (RSP) 0.441, and SAFETY AWARENESS (SAW) 0.601. Furthermore, Pareto analysis revealed that amongst all the feedback statements reviewed, MUTUAL TRUST (MTR) represents 30% of the safety factors attributed to feedback statements that are responsible for 70% of the least performing safety factors found in the weighted safety climate of shipboard staff, while PROMOTION OF SAFETY (POS) and PROBLEM IDENTIFICATION (PID) represent 30% of the safety factors attributed to feedback statements that are responsible for 70% of the least performing safety factors found in the weighted safety climate of shipboard staff. Finally, the TOPSIS methodology was applied to provide maritime administrators with a vessel's ranking, from the least performing to the most performing, for safety culture improvement programs as follows: MT DIDI (0.0908), MT SEA ADVENTURER (0.1124), MT SEAS GRACE (0.1726), MT UMBALWA (0.1815), MT SEA PROGRESS (0.2307), MT SEA VOYAGER (0.3816), MT ASHABI (0.4693), MT MOSUNMOLA (0.5365), MT AMIF (0.9243), and MT KINGIS (1.0000). Conclusively, this thesis adequately demonstrates how decision-making techniques can be simply and successfully applied in assessing the safety culture of maritime organisations without encountering the challenges associated with the availability of safety performance data and the suitability of correlational statistical techniques. It also demonstrated how safety culture could be assessed and managed like other areas of the organisation and business: thereby making safety culture more assessable to continuous improvement programs of maritime organisations with commercial cargo-carrying vessels.Maritime safety culture is currently one of the most important aspects of shipping. It enables maritime administrators to assess and manage safety-related issues proactively. However, most maritime organisations have not been able to effectively assess and manage safety-related issues proactively because of the challenges associated with the availability of safety performance data and the suitability of correlational statistical techniques used in safety culture assessments. Hence, researchers and professionals constantly debate which correlational statistical technique would be most suitable for assessing safety culture. This thesis aims to contribute to safety culture assessment from a methodological perspective of developing a decision-making framework for assessing maritime safety culture. Therefore, this PhD study offers an original contribution to knowledge regarding the application of decision-making techniques in a way that researchers have not previously done in assessing the safety culture of maritime organisations with commercial cargo-carrying vessels. Consequently, the integrated decision-making methodology adopted for this study entailed: the application of Analytical Hierarchy Process (AHP) in establishing weightage and priority setting of safety factors used in further assessments; the application of Simple Additive Weighting (SAW) in establishing the weighted safety climate performance of both shoreside staff and shipboard staff; the application of Pareto analysis in justifying the findings of the weighted safety climate and gaining insights into issues concerning occupational health and safety, ship safety, and shore-to-ship safety; and the application of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in scheduling vessels for safety culture improvement programs. The established weightage and priority setting of safety factors are: COMMUNICATION (COM) 0.15, EMPOWERMENT (EMP) 0.13, FEEDBACK (FDB) 0.11, MUTUAL TRUST (MTR) 0.11, PROBLEM IDENTIFICATION (PID) 0.13, PROMOTION OF SAFETY (POS) 0.12, RESPONSIVENESS (RSP) 0.11, and SAFETY AWARENESS (SAW) 0.14. Subsequently, the weighted safety climate performance of shoreside staff were: (COM) 0.651, EMPOWERMENT (EMP) 0.528, FEEDBACK (FDB) 0.418, MUTUAL TRUST (MTR) 0.365, PROBLEM IDENTIFICATION (PID) 0.543, PROMOTION OF SAFETY (POS) 0.451, RESPONSIVENESS (RSP) 0.448, and SAFETY AWARENESS (SAW) 0.515; while those of shipboard staff were: COMMUNICATION (COM) 0.570, EMPOWERMENT (EMP) 0.523, FEEDBACK (FDB) 0.432, MUTUAL TRUST (MTR) 0.419, PROBLEM IDENTIFICATION (PID) 0.517, PROMOTION OF SAFETY (POS) 0.458, RESPONSIVENESS (RSP) 0.441, and SAFETY AWARENESS (SAW) 0.601. Furthermore, Pareto analysis revealed that amongst all the feedback statements reviewed, MUTUAL TRUST (MTR) represents 30% of the safety factors attributed to feedback statements that are responsible for 70% of the least performing safety factors found in the weighted safety climate of shipboard staff, while PROMOTION OF SAFETY (POS) and PROBLEM IDENTIFICATION (PID) represent 30% of the safety factors attributed to feedback statements that are responsible for 70% of the least performing safety factors found in the weighted safety climate of shipboard staff. Finally, the TOPSIS methodology was applied to provide maritime administrators with a vessel's ranking, from the least performing to the most performing, for safety culture improvement programs as follows: MT DIDI (0.0908), MT SEA ADVENTURER (0.1124), MT SEAS GRACE (0.1726), MT UMBALWA (0.1815), MT SEA PROGRESS (0.2307), MT SEA VOYAGER (0.3816), MT ASHABI (0.4693), MT MOSUNMOLA (0.5365), MT AMIF (0.9243), and MT KINGIS (1.0000). Conclusively, this thesis adequately demonstrates how decision-making techniques can be simply and successfully applied in assessing the safety culture of maritime organisations without encountering the challenges associated with the availability of safety performance data and the suitability of correlational statistical techniques. It also demonstrated how safety culture could be assessed and managed like other areas of the organisation and business: thereby making safety culture more assessable to continuous improvement programs of maritime organisations with commercial cargo-carrying vessels

The 1989 JSC bibliography of scientific and technical papers

This document is a compilation of Lyndon B. Johnson Space Center contributions to the scientific and technical literature in aerospace and life sciences made during calendar year 1989. Citations include NASA formal series reports, journal articles, conference and symposium presentations, papers published in proceedings or other collective works, and seminar and workshop results

Sustainable Assessment in Supply Chain and Infrastructure Management

In the competitive business environment or public domain, the sustainability assessment in supply chain and infrastructure management are important for any organization. Organizations are currently striving to improve their sustainable strategies through preparedness, response, and recovery because of increasing competitiveness, community, and regulatory pressure. Thus, it is necessary to develop a meaningful and more focused understanding of sustainability in supply chain management and infrastructure management practices. In the context of a supply chain, sustainability implies that companies identify, assess, and manage impacts and risks in all the echelons of the supply chain, considering downstream and upstream activities. Similarly, the sustainable infrastructure management indicates the ability of infrastructure to meet the requirements of the present without sacrificing the ability of future generations to address their needs. The complexities regarding sustainable supply chain and infrastructure management have driven managers and professionals to seek different solutions. This Special Issue aims to provide readers with the most recent research results on the aforementioned subjects. In addition, it offers some solutions and also raises some questions for further research and development toward sustainable supply chain and infrastructure management