Fuzzy TOPSIS method for a tourism destination

In this study, we intended to create a methodology in order to have a Multi Criteria approach for choosing a tourist destination region or place as Multi Criteria Decision Making (MCDM) is widely used to outrank, choose or cluster the alternatives with respect to multiple criteria and, in general, refers to making decisions among multi alternatives in the presence of multiple, usually conflicting criteria. Conflicting criteria often makes the problem difficult to decide and select the best alternative among the possible choices. To do this, we propose a Fuzzy TOPSIS Method to choose a Tourism destination in Portugal.info:eu-repo/semantics/publishedVersio

Research on Risk Management for Healthcare Supply Chain in Hospital

Purpose: Unlike the commercial industries, the risks arising from the healthcare industry’s internal system and the surrounding environment may cause serious consequences, even the patients’ health. Concerning the increasing emphasis on risk management in the healthcare supply chain environment, there is an urgent demand for a novel decision support method that supports supply chain risk management in the hospital setting. As the topic is still in the early stage and only a few systematic academic studies on this topic can be found over the last decades. This research aims to propose a novel comprehensive framework and integrated risk management model that takes explicit account of multiple types of risk factors in aiding decision-making as well as compares and ranks the current implemented alternative risk mitigation strategies using fuzzy set theory and multiple criteria decision analysis (MCDA) methods. Methodology: In pursuit of meeting the requirements of the research objectives, this research conducts empirical studies from both China and UK healthcare industries and follows three steps of risk management procedure based on the proposed framework to conduct risk factors identification, assessment and risk mitigation strategies identification. In order to ensure that the analysis is systematic and inclusive, various types of risk factors are identified through a related systematic literature review and are validated through a set of empirical studies. Risk assessment is conducted through two stages of questionnaire surveys and evaluated through Fuzzy Analytic Hierarchy Process (AHP) and Interpretive Structural Modelling (ISM). Thereafter, risk mitigation strategies are identified through conducted empirical studies and evaluated through Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Research Implications: This is the first study which has developed a comprehensive risk management framework in the healthcare supply chain that effectively integrates supply chain risk factors identification, risk assessment as well as mitigation strategy identification and evaluation. The novelty of the developed framework lies in the fact that a systematic and practical decision making tools are proposed supporting hospital managers making strategic decisions on healthcare supply chain risk management. Furthermore, compared with several studies using secondary data, this thesis uses empirical data to conduct the identification and evaluation of risk mitigation strategies, enabling the results closes to the reality of the situation in the healthcare setting. Practical Implications: The profile of risk sources, the priority weighting and inter-relationship among these risks and, the ranking of mitigation strategies provide a guideline for hospital managers to anticipate and proactively deal with potential risks. The proposed framework applies to both the UK and China healthcare industries, the finding can also be applied in other countries and regions

Human Reliability assessment in oil tanker operations

This research is carried out to improve Human Reliability Analysis (HRA) in oil tanker operations in general, to extend and enhance in specific Cognitive Reliability and Error Analysis Method (CREAM), with the aim of reducing human error and thus subsequently preventing oil tanker spills. It is concentrated on oil tanker operations to address the limitation of availability of human reliability data in the maritime domain. The continual occurrence of oil tanker spills, which was substantiated with analysis of historical data of oil tanker incidents/accidents from 1970 to 2008, provides a judicious reason to conduct this research. The critical review of Formal Safety Assessment (FSA) and HRA results in the development of a conceptual framework of HRA facilitating FSA and incorporating Human Organisational Factors (HOF), which addresses the shortcomings of the generic HRA and FSA methodologies that exist independently in the management of oil tankers to prevent oil spills. The CREAM is reviewed due to its prominent use in identifying the root causes of human error. However, its inability of providing solutions to an incident/accident investigation and robust quantification of human reliability features stimulates the development of an advanced CREAM and a human reliability quantification model using a combined Analytic Hierarchical Process (AHP) and fuzzy logic approach in this research. In addition to facilitating identification of the root causes of human error, the advanced CREAM also provides the solutions to a quantification model, which enables the development of HRA data in the maritime domain. Furthermore, lack of CREAM studies on relationships among Common Performance Conditions (CPCs) is addressed by proposing a Decision Making Trial and Evaluation Laboratory (DEMATEL) model, which allows for a comprehensive understanding of relationships and interdependencies among the CPCs. The model could also be used toappreciate and assimilate the relationships and interdependencies among human factor variables involved in other transportation systems and industrial fields. Finally, the research is concluded with an integrated AHP and fuzzy Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) model for determining the selection of an appropriate risk control option (RCO) while performing an incident/accident investigation by taking subjective judgments of decision makers into consideration. This research as a pioneer work in developing and applying advanced techniques to improve the generic CREAM in oil tanker operations establishes a foundation for future effort to improve the use of CREAM in other industries. The techniques developed can also be tailored to investigate and deal with an incident/accident effectively, resulting in the reduction of human error within the system management of any organisatio

PREdictive model for DISaster response configuration (PREDIS decision platform)

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe extraordinary conditions of a disaster, require the mobilisation of all available resources, inducing the rush of humanitarian partners into the affected area. This phenomenon called the proliferation of actors, causes serious problems during the disaster response phase including the oversupply, duplicated efforts, lack of planning. The aim of this research is to provide a solution to reduce the partner proliferation problem. To that end the main research question is put forward as “How to reduce the proliferation of partners in a disaster response”? Panel analysis of the historic record of 4,252 natural onset disasters between 1980 to 2013 via regression analysis, MA and AHP gives rise to the formation of a predictive decision-making platform called PREDIS. It is capable of predicting the human impact of the disaster (fatality, injured, homeless) of up to 3% of errors and enables the decision makers to estimate the required needs for each disaster and prioritises them based on the disaster type and socio-economics of the affected country. It further renders it possible to rank and optimise the desired partners based on the decision maker’s preferences. Verification of the PREDIS through a simulation game design using a sample group of decision makers, show that this technique enables the user to decide within one hour after the disaster strike using the widely available data at the time of the disaster. It also enables non-experts to decide almost identically to experts in terms of the similarity of the choices and the speed of the decision.The lack of an extensive database for the potential humanitarian partners from which to choose, is the limitation of this research in addition to the lack of standardised set of minimum requirements for the suitable partners.The model is also as strong as its data feed which is inconsistent in various humanitarian sources

A decision model to prioritise logistics performance indicators

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonPerformance measurement is an important concern that has recently attracted much attention in the logistics area from both practitioners and academics. The performance measurement of logistics companies is based upon diverse performance indicators. However, to date, limited attention has been paid to the performance measurement of logistics companies and, also, performance measurement processes have become more complex for logistics companies due to the existence of numerous performance indicators. In this regard, the way in which decision makers in logistics companies deal with some vaguenesses, such as deciding on the most important indicators holistically and determining interrelationships between performance indicators, has remained an issue that needs to be resolved. This study, therefore, aims to offer a comprehensive decision model for identifying the key logistics performance indicators and determining the interrelationships among these indicators from logisticians’ perspective. In line with this purpose, the research first presents a stakeholder-based Balanced Scorecard (BSC) model which provides a balanced view by including financial and non-financial performance indicators and a comprehensive approach as a response to the major shortcoming of the generic BSC regarding the negligence of various stakeholders. Then, a large number of performance indicators used in logistics are systematically examined under the proposed model, and the key indicators are selected through an online survey conducted in the Turkish logistics industry. Subsequently, since the performance measurement indicators are not independent of each other, it is critical to understand the causal relationships among different indicators. In such cases, group decision making techniques are capable of modelling such complexities. After a systematic comparison of these techniques, a realistic and easy-to-follow multi-criteria decision making technique, the Analytic Network Process (ANP), is revealed as a suitably powerful method to determine the interrelationships among the indicators. Additionally, a case study approach based on the data obtained from three logistics companies is used to illustrate both the applicability of the model and the practicality of the ANP application. Furthermore, the sensitivity of the results about the case companies is also analysed with several relevant ‘what-if’ scenarios. Thus, real-life practices of three case companies are investigated with the proposed approach. Consequently, this research proposes the BSC-ANP integration which provides a novel way and in-depth understanding to evaluate logistics performance indicators for the competitiveness of logistics companies. Thus, in order to address the aforementioned vaguenesses, the proposed model in this study identifies key performance indicators with the consideration of various stakeholders in the logistics industry to decide on the most important indicators, and evaluates the interrelationships among the indicators by using the ANP. The results of the study show that the educated employee (15.61%) is the most important indicator for the competitiveness of logistics companies and four prominent indicators (educated employee, managerial skills, cost, and profitability) need to be primarily considered by logistics companies. In this way, with this integration, not only the performance indicators in logistics, but also different stakeholders of logistics companies are assessed by the ANP method. This means that the results of this research are not only useful for helping logistics companies to decide which indicators should be focused on to become more competitive, but also can be used as a reference model by different stakeholders in their decision-making processes in order to select the best logistics provider. Keywords: Performance measurement; logistics performance indicators; balanced scorecard (BSC); analytic network process (ANP); multi-criteria decision making (MCDM); stakeholder

A Framework for Improvement of Contractor Selection Procedures on Major Construction Project in Libya.

The construction sector constitutes one of the most important sectors in the economy of any country. Contractor selection is a critical decision that is undertaken by client organisations and is central to the success of any construction project. For major construction projects, final contractor selection often follows the contractor selection stage. Contractor selection is a process which involves investigating, screening and determining whether candidate contractors have the technical and financial capability to be accepted to formally tender for construction work. The process should be conducted prior to the award of contract, characterized by many factors such as: contactor’s skills, experience on similar projects, track- record in the industry, and financial stability. Several models and approaches have been developed to assist client organisations in the contractor selection decision making process. This thesis evaluates the current state of knowledge in relation to contractor selection models.The key features, strengths and limitations of each of these methods are critically evaluated. The key factors of particular interest to client organisations are assessed. This thesis reports on-going research which aims to develop improved contractor selection criteria and methods with specific application to make construction projects in the Libyan context. The aim of this thesis is to build a framework for contractor selection process in the Libyan Construction Industry (LCI) and to find out the major obstacles constraining its operations which so far have not yet been taken into account by the Libyan researchers. However, to address that, a huge investigation has taken place about the current statues for contractor selection in Libya, as well as, in developed and well developed countries. To achieve that, both, theoretical and empirical research was carried out between 2010 and 2013 in Libya. The theoretical study concentrated on the sector of construction industry (Cl) and its key issues, whereas the empirical study focused and explored on the Libyan Construction Industry (LCI) as the context for the study.Two case studies were utilized in this research. The case studies were used to provide more information about the current situation of the LCI and to identify the contractor selection procedures of construction projects in. Also, it assist the researcher to identify key research questions that can later be used in a questionnaire survey.This research was implemented through the administration of a questionnaire survey based on research questions that are required for the building of a framework for contractor selection procedure and the identification of the challenges and obstacles that are facing the clients in the selection process. The development of the framework includes, but is not limited to, contractor selection criteria, decision makers, consultant, clients and sub-contractor. Therefore, the data collection is based on responses from the public and private sector (clients, consultants, contractors and others that are involved in and are knowledgeable about the contractor selection process in the Libyan construction projects). Mean and analysis of variance (independent T-test) were used to manipulate the data from the questionnaire within the SPSS v.20 software environment. The resulting framework was subjected to a validation procedure which involved a structured Delphi technique process based on a focus group consisting of experts who were selected to help with validation of the framework and establishing the extent to which the framework is practical, clear, applicable and comprehensive. This research uses an integrated approach that combines AHP (Analytic Hierarchy Process) method and TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method to evaluate and investigate the current existing practice of contractor selection in Libya. Also, the Delphi technique was used to establish a road map for contractor selection process. Twelve participants were selected to help with validation of the framework. Overall, this research found that the LCI was suffering from a total absence of contractor selection frameworks. This directly impacts on client satisfaction as well as government planning in the reconstruction of the country after the civil war in particular. To close this gap, this research was embarked upon to identify and explore the various contractor selection methods and frameworks that are utilized to support the guidance of contractor selection process toward success. As a consequence of this study, the Contractor Selection Process (CSP) is now very comprehensive and can now be a reference for any problem. Furthermore, this research will help decision makers and others involved to be more aware of and have a better understanding of the selection procedure in the LCI. This new understanding will help decision makers to make more efficacious decisions and to adopt good short and long term policies for contractor selection planning which can then be put into procedure. Even though this framework is built for the LCI, the research can be utilised in other countries that have a similar construction industry environment

Enhancing Managerial Decision-Making Through Multicriteria Modeling

The monograph constitutes a crowning of research led in the field of particular methodology of management science, in the field of enhancing managerial decision-making sub-discipline in frames of the practical stream of the management science discipline. The monograph is a development of the research project in which the elaboration of a scientific method for the enhancement of managerial decision-making processes through the Modular Multicriteria Managerial Decision-Making Model (MMUMADEMM) has been proposed

Multi-criteria decision methods to support the maintenance management of complex systems

[ES] Esta tesis doctoral propone el uso de métodos de toma de decisiones multi-criterio (MCDM, por sus iniciales en inglés) como herramienta estratégica para apoyar la gestión del mantenimiento de sistemas complejos. El desarrollo de esta tesis doctoral se enmarca dentro de un acuerdo de cotutela entre la Università degli Studi di Palermo (UNIPA) y la Universitat Politècnica de València (UPV), dentro de sus respectivos programas de doctorado en 'Ingeniería de Innovación Tecnológica' y 'Matemáticas'. Estos programas están estrechamente vinculados a través del tópico MCDM, ya que proporciona herramientas cruciales para gestionar el mantenimiento de sistemas complejos reales utilizando análisis matemáticos serios. El propósito de esta sinergia es tener en cuenta de forma sólida la incertidumbre al atribuir evaluaciones subjetivas, recopilar y sintetizar juicios atribuidos por varios responsables de la toma de decisiones, y tratar con conjuntos grandes de esos elementos. El tema principal del presente trabajo de doctorado es el gestionamiento de las actividades de mantenimiento para aumentar los niveles de innovación tecnológica y el rendimiento de los sistemas complejos. Cualquier sistema puede ser considerado objeto de estudio, incluidos los sistemas de producción y los de prestación de servicios, entre otros, mediante la evaluación de sus contextos reales. Esta tesis doctoral propone afrontar la gestión del mantenimiento a través del desarrollo de tres líneas principales de investigación estrechamente vinculadas. ¿ La primera es el núcleo, e ilustra la mayoría de los aspectos metodológicos de la tesis. Se refiere al uso de métodos MCDM para apoyar decisiones estratégicas de mantenimiento, y para hacer frente a la incertidumbre que afecta a los datos/evaluaciones, incluso cuando están involucrados varios responsables (expertos en mantenimiento) en la toma de decisiones. ¿ La segunda línea desarrolla análisis de fiabilidad para sistemas complejos reales (también en términos de fiabilidad humana) sobre cuya base se debe implementar cualquier actividad de mantenimiento. Estos análisis consideran la configuración de fiabilidad de los componentes del sistema en estudio y las características específicas del entorno operativo. ¿ La tercera línea de investigación aborda aspectos metodológicos importantes de la gestión de mantenimiento y enfatiza la necesidad de monitorizar el funcionamiento de las actividades de mantenimiento y de evaluar su efectividad utilizando indicadores adecuados. Se ha elaborado una amplia gama de casos de estudio del mundo real para evaluar la eficacia de los métodos MCDM en el mantenimiento y así probar la utilidad del enfoque propuesto.[CA] Aquesta tesi doctoral proposa l'ús de mètodes de presa de decisions multi-criteri (MCDM, per les seves inicials en anglès) com a eina estratègica per donar suport a la gestió del manteniment de sistemes complexos. El desenvolupament d'aquesta tesi doctoral s'emmarca dins d'un acord de cotutela entre la Università degli Studi di Palermo (UNIPA) i la Universitat Politècnica de València (UPV), dins dels seus respectius programes de doctorat en 'Enginyeria d'Innovació Tecnològica' i ' Matemàtiques '. Aquests programes estan estretament vinculats a través del tòpic MCDM, ja que proporciona eines crucials per gestionar el manteniment de sistemes complexos reals utilitzant anàlisis matemàtics profunds. El propòsit d'aquesta sinergia és tenir en compte de forma sòlida la incertesa en atribuir avaluacions subjectius, recopilar i sintetitzar judicis atribuïts per diversos responsables de la presa de decisions, i tractar amb conjunts grans d'aquests elements en els problemes plantejats. El tema principal del present treball de doctorat es la gestió de les activitats de manteniment per augmentar els nivells d'innovació tecnològica i el rendiment dels sistemes complexos. Qualsevol sistema pot ser considerat objecte d'estudi, inclosos els sistemes de producció i els de prestació de serveis, entre d'altres, mitjançant l'avaluació dels seus contextos reals. Aquesta tesi doctoral proposa afrontar la gestió del manteniment mitjançant el desenvolupament de tres línies principals d'investigació estretament vinculades. ¿ La primera és el nucli, i il·lustra la majoria dels aspectes metodològics de la tesi. Es refereix a l'ús de mètodes MCDM per donar suport a decisions estratègiques de manteniment, i per fer front a la incertesa que afecta les dades/avaluacions, fins i tot quan estan involucrats diversos responsables (experts en manteniment) en la presa de decisions. ¿ La segona línia desenvolupa anàlisis de fiabilitat per a sistemes complexos reals (també en termes de fiabilitat humana) sobre la qual base s'ha d'implementar qualsevol activitat de manteniment. Aquestes anàlisis consideren la configuració de fiabilitat dels components del sistema en estudi i les característiques específiques de l'entorn operatiu. ¿ La tercera línia d'investigació aborda aspectes metodològics importants de la gestió de manteniment i emfatitza la necessitat de monitoritzar el funcionament de les activitats de manteniment i d'avaluar la seva efectivitat utilitzant indicadors adequats. S'ha elaborat una àmplia gamma de casos d'estudi del món real per avaluar l'eficàcia dels mètodes MCDM en el manteniment i així provar la utilitat de l'enfocament proposat.[EN] This doctoral thesis proposes using multi-criteria decision making (MCDM) methods as a strategic tool to support maintenance management of complex systems. The development of this doctoral thesis is framed within a cotutelle (co-tutoring) agreement between the Università degli Studi di Palermo (UNIPA) and the Universitat Politècnica de València (UPV), within their respective programmes of doctorates in 'Technological Innovation Engineering' and 'Mathematics'. Regarding this thesis, these programmes are closely linked through the topic of MCDM, providing crucial tools to manage maintenance of real complex systems by applying in-depth mathematical analyses. The purpose of this connection is to robustly take into account uncertainty in attributing subjective evaluations, collecting and synthetizing judgments attributed by various decision makers, and dealing with large sets of elements characterising the faced issue. The main topic of the present doctoral work is the management of maintenance activities to increase the levels of technological innovation and performance of the analysed complex systems. All kinds of systems can be considered as objects of study, including production systems and service delivery systems, among others, by evaluating their real contexts. Thus, this doctoral thesis proposes facing maintenance management through the development of three tightly linked main research lines. ¿ The first is the core and illustrates most of the methodological aspects of the thesis. It refers to the use of MCDM methods for supporting strategic maintenance decisions, and dealing with uncertainty affecting data/evaluations even when several decision makers are involved (experts in maintenance). ¿ The second line develops reliability analyses for real complex systems (also in terms of human reliability analysis) on the basis of which any maintenance activity must be implemented. These analyses are approached by considering the reliability configuration of both the components belonging to the system under study and the specific features of the operational environment. ¿ The third research line focuses on important methodological aspects to support maintenance management, and emphasises the need to monitor the performance of maintenance activities and evaluate their effectiveness using suitable indicators. A wide range of real real-world case studies has been faced to evaluate the effectiveness of MCDM methods in maintenance and then prove the usefulness of the proposed approach.Carpitella, S. (2019). Multi-criteria decision methods to support the maintenance management of complex systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11911