44 research outputs found

    Using Fuzzy Delphi and Generalized Fuzzy TOPSIS to Evaluate Technological Service Flexibility Dimensions of Internet Malls

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    The expanding development of technology and availability of the internet is leading a consumer shift from offline to online activity. This shifting behavior shows positive signs for the growth of the e-commerce market but also increases the challenges for the online service provider to provide satisfaction and loyalty to consumers when there is no personal interaction between buyer and seller. In these circumstances, quality, in terms of technology services i.e. web/transaction, can play a significant role for the service provider, especially for internet shopping malls. But there is little material available in current literature to build a theoretical model for web/transaction flexibility dimensions and to rank internet shopping malls on their provision of services to customers. The vagueness of the available information can be tackled by fuzzy theory by employing a Fuzzy Delphi method to finalize technological service dimensions and lead to development of a research model. The final ranking of internet malls has been achieved by utilizing Generalized Fuzzy TOPSIS. The findings of this study can be useful for internet shopping malls in devising strategies to provide a better quality of web/transaction service to customers.N/

    Modelo basado en la toma decisiones con criterios múltiples para la elección de metodologías de data science

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    La capacidad de almacenamiento de datos generados por las organizaciones ha aumentado de manera significativa en las últimas décadas y poder analizarlos de manera adecuada, genera un factor estratégico para la Toma de Decisiones (TD). Se puede observar que en los últimos años se ha incrementado la cantidad de profesionales vinculados a la Ciencia de Datos (Data Science) y una de las habilidades requeridas es conocer y manejar a la perfección las metodologías disponibles y determinar cuál se adapta mejor para cada proyecto. Es por ello que al existir una diversidad de metodologías propuestas para el desarrollo de proyectos, en ocasiones la elección no es tarea sencilla, especialmente para los que se inician en el área. La presente investigación tiene como objetivo establecer un modelo basado en la Toma de Decisiones Multicriterios (o criterios múltiples), a través de métodos como el Proceso Analítico Jerárquico y su variante combinado con Lógica Difusa, con el propósito de establecer una base sólida para la selección de metodologías que guíen los proyectos de Minería de Datos o Data Science.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informátic

    Modelo basado en la toma decisiones con criterios múltiples para la elección de metodologías de data science

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    La capacidad de almacenamiento de datos generados por las organizaciones ha aumentado de manera significativa en las últimas décadas y poder analizarlos de manera adecuada, genera un factor estratégico para la Toma de Decisiones (TD). Se puede observar que en los últimos años se ha incrementado la cantidad de profesionales vinculados a la Ciencia de Datos (Data Science) y una de las habilidades requeridas es conocer y manejar a la perfección las metodologías disponibles y determinar cuál se adapta mejor para cada proyecto. Es por ello que al existir una diversidad de metodologías propuestas para el desarrollo de proyectos, en ocasiones la elección no es tarea sencilla, especialmente para los que se inician en el área. La presente investigación tiene como objetivo establecer un modelo basado en la Toma de Decisiones Multicriterios (o criterios múltiples), a través de métodos como el Proceso Analítico Jerárquico y su variante combinado con Lógica Difusa, con el propósito de establecer una base sólida para la selección de metodologías que guíen los proyectos de Minería de Datos o Data Science.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informátic

    Modelo basado en la toma decisiones con criterios múltiples para la elección de metodologías de data science

    Get PDF
    La capacidad de almacenamiento de datos generados por las organizaciones ha aumentado de manera significativa en las últimas décadas y poder analizarlos de manera adecuada, genera un factor estratégico para la Toma de Decisiones (TD). Se puede observar que en los últimos años se ha incrementado la cantidad de profesionales vinculados a la Ciencia de Datos (Data Science) y una de las habilidades requeridas es conocer y manejar a la perfección las metodologías disponibles y determinar cuál se adapta mejor para cada proyecto. Es por ello que al existir una diversidad de metodologías propuestas para el desarrollo de proyectos, en ocasiones la elección no es tarea sencilla, especialmente para los que se inician en el área. La presente investigación tiene como objetivo establecer un modelo basado en la Toma de Decisiones Multicriterios (o criterios múltiples), a través de métodos como el Proceso Analítico Jerárquico y su variante combinado con Lógica Difusa, con el propósito de establecer una base sólida para la selección de metodologías que guíen los proyectos de Minería de Datos o Data Science.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informátic

    A Multi-Criteria Decision Making Approach to Feedstock Selection

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    Selection of the appropriate feedstock for biodiesel production, taking into consideration several potentially conflicting quantitative and qualitative criteria, is a complex multiple-criteria decision making (MCDM) problem that requires an extensive evaluation process of a group of decision makers (DMs). In this paper, as the MCDM method, fuzzy Analytic Hierarchy Process (F-AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) methods are integrated to evaluate plant based feedstock alternatives for biodiesel production in Turkey. The F-AHP method is used to determine the importance weights of criteria, and the F-TOPSIS method is implemented to evaluate and rank feedstock alternatives with respect to a set of qualitative and quantitative benefit criteria. More specifically, in this paper, plant based feedstocks in Turkey: Sunflower, peanut, cottonseed, canola, safflower, soybean, and poppy seed are evaluated and ranked by decision makers (DMs) with respect to several benefit criteria: Price adequacy, suitability of the plant to the climate and environment, benefits of the plant after processing (the sediment), suitability of the feedstock for technological processing, and yield efficiency, implementing the integrated fuzzy AHP-TOPSIS method

    The impact of enterprise resource planning system on Iranian firms performance

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    In the past two decades, there has been a significant growth market for Enterprise Resource Planning (ERP) in developing countries. However, due to recent economic development of these countries such as Iran, the demand for ERP systems increased considerably. Besides these growths, failures in ERP implementation also have been increased. Therefore, there is an urgent need for understanding ERP implementation and post evaluation issues in developing countries. The main objectives of this study is to identify common ERP modules, critical success factors (CSFs) of ERP implementation among the manufacturing firms in Iran in order to assess the impact of ERP systems implementation on performance across four perspectives (financial, customer, internal process and learning) of the balanced scorecard (BSC). For this purpose, a theory-based model has been developed to examine the relationship between ERP system status and firms performance perspectives. Empirical analyses are based on survey data drawn from 93 Iranian manufacturing firms, which have adopted ERP systems for at least a year. Structural equation modeling (SEM) is employed to test the research hypotheses and Fuzzy DEMATEL method is applied to find the impact of ERP implementation modules and performance indicators. The result indicates that there is a positive significant relationship between ERP system status and changes in financial, customer and learning perspectives of performance. In addition, CSFs and ERP modules on performance perspectives indicated a positive interaction. On the other hand, fuzzy DEMATEL analysis shows, sale and distribution module of ERP had the strongest impact on performance within Iranian manufacturing firms. Consequently, the managers who want to implement ERP systems can use the ranking to choose suitable ERP modules. The results of the study suggest that firms that emphasize CSFs throughout the ERP implementation process achieve higher performance improvement. Further research should gather data from various sources and also from the service sectors

    Turismo y Sistemas Empresariales Resilientes: Factores Críticos de Adaptabilidad en Baños de Agua Santa – Ecuador

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    Resilience is understood as dynamic learning ability, self-organization and adaptability of a system, when affected by unforeseen events. Within this context, this research focuses on business dimension of resilience and establishes a methodology based on Fuzzy AHP to determine the incidence of five analysis criteria that related to: business vision, opportunity entrepreneurship, business environment, company behavior disaster response and female entrepreneurship, according to scientific literature and expert opinion, are immersed in the adaptability of the territories and regions affected by natural disasters. The empirical application in the turistic town of Baños de Agua Santa in Ecuador, is justified to be recognized by the United Nations as "Resilient City to volcanic events". The results present an assessment of the resilience of business system in this town, while identifying how these factors contributed to its adaptability. Fuzzy AHP model considers expert judgment catastrophic events in Ecuador and Chile in the last sixteen years.La resiliencia es entenidda como la capacidad dinámica de aprendizaje, auto-organización y adaptabilidad de un sistema, cuando es afectado por eventos imprevistos. Dentro de este contexto, esta investigación se enfoca en la dimensión económico-empresarial de la resiliencia y establece una metodología basada en Fuzzy AHP para determinar la incidencia de cinco criterios de análisis que se relacionan con: visión empresarial, emprendimiento por oportunidad, ambiente empresarial, comportamiento de la empresa frente al desastre y actividad empresarial femenina, que de acuerdo a la literatura científica y a la opinión de expertos, están inmersos en la adaptabilidad de los territorios y regiones afectados por desastres de origen natural.  La aplicación empírica en la ciudad turística de Baños de Agua Santa en Ecuador,  se justifica al ser reconocida por la Naciones Unidas, como “Ciudad Resiliente a eventos volcánicos”. Los resultados presentan un diagnóstico de la resiliencia del sistema económico-empresarial de esta localidad, a la vez que identifican en qué medida estos factores contribuyeron a su adaptabilidad. El modelo Fuzzy AHP, considera el juicio de expertos en eventos catastróficos ocurridos en Ecuador y Chile en estos últimos dieciseis años.

    Strategic Logistics Outsourcing:Integrated Models for Evaluating and Selecting Logistics Service Providers (LSPs) Upstream/Downstream Supply Chain Comparison

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    This research aims to maximize the logistics outsourcing benefits through developing new hybrid models for evaluating and selecting Logistics Service Providers (LSPs). The growing demand for logistics outsourcing and the increase in the number and type of LSPs highlight the increasing importance of the LSP evaluation and selection process. Firms use various approaches to evaluate and select their LSP partners. Most of these approaches seem to have overlooked the strategic side of the logistics outsourcing process. Additionally, the uncertainty issue of data, the complexity of the decision and the large number of criteria involved increase the attractiveness of the Multi-Criteria Decision-Making (MCDM) approaches. A comparative literature review was used in order to identify crucial factors and methods that are used in logistics literature in fragmented ways and therefore, to establish and design a conceptual framework and models for logistics outsourcing. First, a long list of evaluation criteria was developed. Three main dimensions were identified: logistics performance, logistics resources and logistics services. Then a conceptual framework was developed using the three main dimensions with their related factors. Based on the comparative literature review outcomes, a number of integrated models have been developed and used to achieve this aim with emphasis given to FDEMATEL, FTOPSIS and FQFD techniques. Whereas the FDEMATEL technique contributed to construct influence relationships between factors under each dimension, develop impact-relationship maps and identify dependent and independent success factors (ISFs), the FTOPSIS technique used the weighted success factors to evaluate, rank and select the best LSP in three case studies. Twenty-one ISFs have been identified to be used in the final approach. These ISFs consist of eight LKPIs, seven logistics services and six logistics resources and capabilities. All of the factors were used to evaluate and select the best LSP alternative and ISFs were used to conduct the evaluation process. Different sensitivity analysis tests are used to confirm models’ robustness. Based on the outcomes of both cases, decision makers can use independent factors alone to evaluate and select the best LSP, which simplified the logistics outsourcing process in our study. The FQFD technique was used to link the LSUs strategic objectives with logistics requirements and the ISFs to develop a new strategic logistics outsourcing approach. Finally, two case studies representing the supply chain upstream and downstream are used to demonstrate the new hybrid approach effectiveness. The comparison of both cases’ findings highlighted their differences in terms of strategic objectives, logistics requirements and ISFs

    Studies on some aspects of agility appraisement: empirical research and case studies in Indian perspective

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    The thesis highlights decision-making problems in relation to agility evaluation as well as appraisement of agile enterprises followed be suppliers’ selection in agile supply chain. Various aspects have been covered (i) Supply Chain Agility Appraisement and (ii) Appraisement of Agility in Mass Customized Product Manufacturing (iii) Organizational Agility and Benchmarking of Agile Enterprises, (iv) Interrelationship amongst Agile Capabilities/Enablers, (v) Identification of Agile Barriers etc. Appraisement modules (appraisement index systems) have been proposed utilizing the concept of generalized fuzzy numbers, Interval-Valued Fuzzy Numbers (IVFNs) as well as grey numbers. The study provides in-depth understanding on hierarchical interrelationship amongst various agility dimensions required to assess organizational as well as supply chain agility. Agility appraisement modules have been proposed to perform both in fuzzy as well as grey environment. Agility barriers have been identified as well. The outcome of the empirical research as well as case study conducted in two Indian industries (automotive and railway construction at eastern India) have been critically analyzed. The influence of decision-makers’ risk bearing attitude over agility assessment and related decision-making has also been focused in this work. An efficient fuzzy embedded performance appraisement module has been proposed to facilitate suppliers’ evaluation cum selection process in agile supply chain. There exist a number of agility indices (metrics) that influence the extent of organizational agility. By evaluating these indices, appropriate ranking order of alternative agile enterprises can be determined. This being the basic fundamental of Multi-Criteria Decision Making (MCDM), it can effectively be explored towards benchmarking of agile enterprises. Evaluating the candidate agile alternatives and comparing across them, the best practices of the efficient organization can easily be identified and transferred to different organizations. Indian manufacturing industries prefer to maintain status-quo and hardly go for changes (or transformation). However, today’s market compulsion due to liberalization and globalization of demands that manufacturing firms must be agile enough to serve continuously changing unpredicted needs of the customers in an effective manner. The changes in terms of being agile are not easy enough due to several environmental, managerial and technical considerations. Analysis of drivers of agile manufacturing and their interaction with various aspects in integrative planning can be a valuable source of information to the decision-makers (DMs) for its successful implementation. In doing so, the managers can derive important insights into the problem and explore the said drivers efficiently to overcome those obstacles. Agility evaluation problem can be viewed as a multi-criteria decision making (MCDM) problem involving qualitative as well as quantitative evaluation criterions. Quantitative criterions (attributes) can be tackled by traditional tools and approaches. Difficulty arises in dealing with subjective qualitative selection criterions. In this thesis, fuzzy logic (as well as grey theory) has been proposed to tackle decision-makers’ subjective information/judgment in relation to agility appraisement and related decision-making vi problems. Literature is rich enough in addressing various decision-modeling problems using generalized fuzzy numbers; therefore, fruitful incorporation of Interval-Valued Fuzzy Numbers theory and grey theory definitely added value (contribution) pursued in data analysis (empirical as well as case studies) in this thesis. Use of ‘Fuzzy Degree of Similarity’ concept in identifying weak (ill-performing) areas (called agile barriers) in an agile supply chain appears to be a unique contribution in this work

    Rethinking the risk matrix

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    So far risk has been mostly defined as the expected value of a loss, mathematically PL (being P the probability of an adverse event and L the loss incurred as a consequence of the adverse event). The so called risk matrix follows from such definition. This definition of risk is justified in a long term “managerial” perspective, in which it is conceivable to distribute the effects of an adverse event on a large number of subjects or a large number of recurrences. In other words, this definition is mostly justified on frequentist terms. Moreover, according to this definition, in two extreme situations (high-probability/low-consequence and low-probability/high-consequence), the estimated risk is low. This logic is against the principles of sustainability and continuous improvement, which should impose instead both a continuous search for lower probabilities of adverse events (higher and higher reliability) and a continuous search for lower impact of adverse events (in accordance with the fail-safe principle). In this work a different definition of risk is proposed, which stems from the idea of safeguard: (1Risk)=(1P)(1L). According to this definition, the risk levels can be considered low only when both the probability of the adverse event and the loss are small. Such perspective, in which the calculation of safeguard is privileged to the calculation of risk, would possibly avoid exposing the Society to catastrophic consequences, sometimes due to wrong or oversimplified use of probabilistic models. Therefore, it can be seen as the citizen’s perspective to the definition of risk
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