Data driven approaches for smart city planning and design: a case scenario on urban data management

Purpose Because of the use of digital technologies in smart cities, municipalities are increasingly facing issues related to urban data management and are seeking ways to exploit these huge amounts of data for the actualization of data driven services. However, only few studies discuss challenges related to data driven strategies in smart cities. Accordingly, the purpose of this study is to present data driven approaches (architecture and model), for urban data management needed to improve smart city planning and design. The developed approaches depict how data can underpin sustainable urban development. Design/methodology/approach Design science research is adopted following a qualitative method to evaluate the architecture developed based on top-level design using a case data from workshops and interviews with experts involved in a smart city project. Findings The findings of this study from the evaluations indicate that the identified enablers are useful to support data driven services in smart cities and the developed architecture can be used to promote urban data management. More importantly, findings from this study provide guidelines to municipalities to improve data driven services for smart city planning and design. Research limitations/implications Feedback as qualitative data from practitioners provided evidence on how data driven strategies can be achieved in smart cities. However, the model is not validated. Hence, quantitative data is needed to further validate the enablers that influence data driven services in smart city planning and design. Practical implications Findings from this study offer practical insights and real-life evidence to define data driven enablers in smart cities and suggest research propositions for future studies. Additionally, this study develops a real conceptualization of data driven method for municipalities to foster open data and digital service innovation for smart city development. Social implications The main findings of this study suggest that data governance, interoperability, data security and risk assessment influence data driven services in smart cities. This study derives propositions based on the developed model that identifies enablers for actualization of data driven services for smart cities planning and design. Originality/value This study explores the enablers of data driven strategies in smart city and further developed an architecture and model that can be adopted by municipalities to structure their urban data initiatives for improving data driven services to make cities smarter. The developed model supports municipalities to manage data used from different sources to support the design of data driven services provided by different enterprises that collaborate in urban environment.acceptedVersio

Barriers to blockchain adoption in humanitarian logistics in an uncertain environment

In the digital age, blockchain technology is recognized as an operational innovation that is rapidly joining the field of supply chain and humanitarian logistics. Hence, blockchain technology has the potential to fundamentally change the field of humanitarian aid, but still relatively little research has been published aimed at improving understanding of the various barriers to blockchain adoption in humanitarian logistics. The aim of this research is to provide an integrated framework for evaluating the barriers to blockchain adoption in the field of humanitarian logistics. To assess the barriers, integrated approach has been applied in three phases. In the first phase of this approach, based on the literature, 10 barriers to the adoption of blockchain in humanitarian logistics are identified and evaluated using the FMEA method. In the second phase, using the opinions of experts, the weights of the three factors are calculated. Then, in the third phase and according to the outputs of the previous phases, obstacles are prioritized using the proposed Z-ARAS method. In addition to assigning different weights to the three factors considering uncertainty and reliability in barriers is also considered in this approach through the theory of Z numbers. The proposed approach of current study was implemented in the evaluation of blockchain adoption barriers in humanitarian logistics. According to the results, the most critical barriers concern with integrating issues, risk of cyber-attacks, and technology risks. The results shown the capability and superiority of the proposed approach compared to other traditional methods such as FMEA and Fuzzy ARAS

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

Fuzzy Sets in Business Management, Finance, and Economics

This book collects fifteen papers published in s Special Issue of Mathematics titled “Fuzzy Sets in Business Management, Finance, and Economics”, which was published in 2021. These paper cover a wide range of different tools from Fuzzy Set Theory and applications in many areas of Business Management and other connected fields. Specifically, this book contains applications of such instruments as, among others, Fuzzy Set Qualitative Comparative Analysis, Neuro-Fuzzy Methods, the Forgotten Effects Algorithm, Expertons Theory, Fuzzy Markov Chains, Fuzzy Arithmetic, Decision Making with OWA Operators and Pythagorean Aggregation Operators, Fuzzy Pattern Recognition, and Intuitionistic Fuzzy Sets. The papers in this book tackle a wide variety of problems in areas such as strategic management, sustainable decisions by firms and public organisms, tourism management, accounting and auditing, macroeconomic modelling, the evaluation of public organizations and universities, and actuarial modelling. We hope that this book will be useful not only for business managers, public decision-makers, and researchers in the specific fields of business management, finance, and economics but also in the broader areas of soft mathematics in social sciences. Practitioners will find methods and ideas that could be fruitful in current management issues. Scholars will find novel developments that may inspire further applications in the social sciences

Optimal sensor placement for sewer capacity risk management

2019 Spring.Includes bibliographical references.Complex linear assets, such as those found in transportation and utilities, are vital to economies, and in some cases, to public health. Wastewater collection systems in the United States are vital to both. Yet effective approaches to remediating failures in these systems remains an unresolved shortfall for system operators. This shortfall is evident in the estimated 850 billion gallons of untreated sewage that escapes combined sewer pipes each year (US EPA 2004a) and the estimated 40,000 sanitary sewer overflows and 400,000 backups of untreated sewage into basements (US EPA 2001). Failures in wastewater collection systems can be prevented if they can be detected in time to apply intervention strategies such as pipe maintenance, repair, or rehabilitation. This is the essence of a risk management process. The International Council on Systems Engineering recommends that risks be prioritized as a function of severity and occurrence and that criteria be established for acceptable and unacceptable risks (INCOSE 2007). A significant impediment to applying generally accepted risk models to wastewater collection systems is the difficulty of quantifying risk likelihoods. These difficulties stem from the size and complexity of the systems, the lack of data and statistics characterizing the distribution of risk, the high cost of evaluating even a small number of components, and the lack of methods to quantify risk. This research investigates new methods to assess risk likelihood of failure through a novel approach to placement of sensors in wastewater collection systems. The hypothesis is that iterative movement of water level sensors, directed by a specialized metaheuristic search technique, can improve the efficiency of discovering locations of unacceptable risk. An agent-based simulation is constructed to validate the performance of this technique along with testing its sensitivity to varying environments. The results demonstrated that a multi-phase search strategy, with a varying number of sensors deployed in each phase, could efficiently discover locations of unacceptable risk that could be managed via a perpetual monitoring, analysis, and remediation process. A number of promising well-defined future research opportunities also emerged from the performance of this research

Framing the FRAM: A literature review on the functional resonance analysis method

The development of the Functional Resonance Analysis Method (FRAM) has been motivated by the perceived limitations of fundamentally deterministic and probabilistic approaches to understand complex systems’ behaviour. Congruent with the principles of Resilience Engineering, over recent years the FRAM has been progressively developed in scientific terms, and increasingly adopted in industrial environments with reportedly successful results. Nevertheless, a wide literature review focused on the method is currently lacking. On these premises, this paper aims to summarise all available published research in English about FRAM. More than 1700 documents from multiple scientific repositories were reviewed through a protocol based on the PRISMA review technique. The paper aims to uncover a number of characteristics of the FRAM research, both in terms of the method's application and of the authors contributing to its development. The systematic analysis explores the method in terms of its methodological aspects, application domains, and enhancements in qualitative and quantitative terms, as well as proposing potential future research directions

Decision Making Analysis for an Integrated Risk Management Framework of Maritime Container Port Infrastructure and Transportation Systems

This research proposes a risk management framework and develops generic risk-based decision-making, and risk-assessment models for dealing with potential Hazard Events (HEs) and risks associated with uncertainty for Operational Safety Performance (OSP) in container terminals and maritime ports. Three main sections are formulated in this study: Section 1: Risk Assessment, in the first phase, all HEs are identified through a literature review and human knowledge base and expertise. In the second phase, a Fuzzy Rule Base (FRB) is developed using the proportion method to assess the most significant HEs identified. The FRB leads to the development of a generic risk-based model incorporating the FRB and a Bayesian Network (BN) into a Fuzzy Rule Base Bayesian Network (FRBN) method using Hugin software to evaluate each HE individually and prioritise their specific risk estimations locally. The third phase demonstrated the FRBN method with a case study. The fourth phase concludes this section with a developed generic risk-based model incorporating FRBN and Evidential Reasoning to form an FRBER method using the Intelligence Decision System (IDS) software to evaluate all HEs aggregated collectively for their Risk Influence (RI) globally with a case study demonstration. In addition, a new sensitivity analysis method is developed to rank the HEs based on their True Risk Influence (TRI) considering their specific risk estimations locally and their RI globally. Section 2: Risk Models Simulations, the first phase explains the construction of the simulation model Bayesian Network Artificial Neural Networks (BNANNs), which is formed by applying Artificial Neural Networks (ANNs). In the second phase, the simulation model Evidential Reasoning Artificial Neural Networks (ERANNs) is constructed. The final phase in this section integrates the BNANNs and ERANNs that can predict the risk magnitude for HEs and provide a panoramic view on the risk inference in both perspectives, locally and globally. Section 3: Risk Control Options is the last link that finalises the risk management based methodology cycle in this study. The Analytical Hierarchal Process (AHP) method was used for determining the relative weights of all criteria identified in the first phase. The last phase develops a risk control options method by incorporating Fuzzy Logic (FL) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to form an FTOPSIS method. The novelty of this research provides an effective risk management framework for OSP in container terminals and maritime ports. In addition, it provides an efficient safety prediction tool that can ease all the processes in the methods and techniques used with the risk management framework by applying the ANN concept to simulate the risk models

Risk Management for the Future

A large part of academic literature, business literature as well as practices in real life are resting on the assumption that uncertainty and risk does not exist. We all know that this is not true, yet, a whole variety of methods, tools and practices are not attuned to the fact that the future is uncertain and that risks are all around us. However, despite risk management entering the agenda some decades ago, it has introduced risks on its own as illustrated by the financial crisis. Here is a book that goes beyond risk management as it is today and tries to discuss what needs to be improved further. The book also offers some cases