763 research outputs found
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Indicator based multi-criteria decision support systems for wastewater treatment plants
Data availability:
Data will be made available on request.Wastewater treatment plant decision makers face stricter regulations regarding human health protection, environmental preservation, and emissions reduction, meaning they must improve process sustainability and circularity, whilst maintaining economic performance. This creates complex multi-objective problems when operating and selecting technologies to meet these demands, resulting in the development of many decision support systems for the water sector. European Commission publications highlight their ambition for greater levels of sustainability, circularity, and environmental and human health protection, which decision support system implementation should align with to be successful in this region. Following the review of 57 wastewater treatment plant decision support systems, the main function of multi-criteria decision-making tools are technology selection and the optimisation of process operation. A large contrast regarding their aims is found, as process optimisation tools clearly define their goals and indicators used, whilst technology selection procedures often use vague language making it difficult for decision makers to connect selected indicators and resultant outcomes. Several recommendations are made to improve decision support system usage, such as more rigorous indicator selection protocols including participatory selection approaches and expansion of indicators sets, as well as more structured investigation of results including the use of sensitivity or uncertainty analysis, and error quantification.Horizon 2020 research and innovation programme DEEP PURPLE. The H2020 DEEP PURPLE project has received funding from the Bio-based Industries Joint Undertaking (JU) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 837998. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio-based Industries Consortium
Transforming medical equipment management in digital public health: a decision-making model for medical equipment replacement
IntroductionIn the rapidly evolving field of digital public health, effective management of medical equipment is critical to maintaining high standards of healthcare service levels and operational efficiency. However, current decisions to replace large medical equipment are often based on subjective judgments rather than objective analyses and lack a standardized approach. This study proposes a multi-criteria decision-making model that aims to simplify and enhance the medical equipment replacement process.MethodsThe researchers developed a multi-criteria decision-making model specifically for the replacement of medical equipment. The model establishes a system of indicators for prioritizing and evaluating the replacement of large medical equipment, utilizing game theory to assign appropriate weights, which uniquely combines the weights of the COWA and PCA method. In addition, which uses the GRA method in combination with the TOPSIS method for a more comprehensive decision-making model.ResultsThe study validates the model by using the MRI equipment of a tertiary hospital as an example. The results of the study show that the model is effective in prioritizing the most optimal updates to the equipment. Significantly, the model shown a higher level of differentiation compared to the GRA and TOPSIS methods alone.DiscussionThe present study shows that the multi-criteria decision-making model presented provides a powerful and accurate tool for optimizing decisions related to the replacement of large medical equipment. By solving the key challenges in this area as well as giving a solid basis for decision making, the model makes significant progress toward the field of management of medical equipment
The analysis of critical success factors for successful kaizen implementation during the COVID-19 pandemic: a textile industry case study
Purpose
The primary objective of this research is to determine critical success factors (CSFs) that enable textile enterprises to effectively implement Kaizen, a Japanese concept of continuous development, particularly during disruptive situations. The study aims to provide insights into how Kaizen is specifically employed within the textile sector and to offer guidance for addressing future crises.
Design/methodology/approach
This study employs a structured approach to determine CSFs for successful Kaizen implementation in the textile industry. The Triple Helix Actors structure, comprising business, academia and government representatives, is utilized to uncover essential insights. Additionally, the Matriced Impacts Croises-Multiplication Applique and Classement (MICMAC) analysis and interpretative structural modeling (ISM) techniques are applied to evaluate the influence of CSFs.
Findings
The research identifies 17 CSFs for successful Kaizen implementation in the textile industry through a comprehensive literature review and expert input. These factors are organized into a hierarchical structure with 5 distinct levels. Additionally, the application of the MICMAC analysis reveals three clusters of CSFs: linkage, dependent and independent, highlighting their interdependencies and impact.
Originality/value
Major contribution of this study is understanding how Kaizen can be effectively utilized in the textile industry, especially during disruptive events. The combination of the Triple Helix Actors structure, MICMAC analysis and ISM provides a unique perspective on the essential factors driving successful Kaizen implementation. The identification of CSFs and their categorization into clusters offer valuable insights for practitioners, policymakers and academia seeking to enhance the resilience and sustainability of the textile industry
Innovation Performance Analysis of G20 Countries: A Novel Integrated LOPCOW-MAIRCA MCDM Approach Including the COVID-19 Period
Purpose: This study aims to examine the innovation performance of G20 countries in 2018-2022 with multi criteria decision making methods. When the 5-year performance was analyzed, it was also revealed whether the COVID-19 outbreak has an impact on the innovation performance of the countries.
Methodology: An integrated LOPCOW (Logarithmic Percentage Change-driven Objective Weighting) - MAIRCA (Multi Attribute Ideal-Real Comparative Analysis) method was applied in the study. First, the indicators representing innovation performance (institutions, human capital, and research, infrastructure, market sophistication, business sophistication, knowledge and technology outputs, creative outputs) was objectively weighted by the LOPCOW method. Then, the innovation performance of G20 countries was calculated with the MAIRCA method. Finally, a comparative analysis was also presented to support the findings.
Findings: As a result of the innovation performance analysis using multi criteria decision making methods, human capital, and research were found to be the most important indicators, and the United States was found to be the country with the best innovation performance. In the sensitivity and comparative analysis, it was concluded that the integrated LOPCOW-MAIRCA method provides robust outputs.
Originality: This study makes original contributions by analyzing the impact of the COVID-19 pandemic on the innovation performance of countries considering the 2018-2022 period and the integrated multi criteria decision making methods it uses that have not yet been applied in the literature
MASISCo—Methodological Approach for the Selection of Information Security Controls
As cyber-attacks grow worldwide, companies have begun to realize the importance of being protected against malicious actions that seek to violate their systems and access their information assets. Faced with this scenario, organizations must carry out correct and efficient management of their information security, which implies that they must adopt a proactive attitude, implementing standards that allow them to reduce the risk of computer attacks. Unfortunately, the problem is not only implementing a standard but also determining the best way to do it, defining an implementation path that considers the particular objectives and conditions of the organization and its availability of resources. This paper proposes a methodological approach for selecting and planning security controls, standardizing and systematizing the process by modeling the situation (objectives and constraints), and applying optimization techniques. The work presents an evaluation of the proposal through a methodology adoption study. This study showed a tendency of the study subjects to adopt the proposal, perceiving it as a helpful element that adapts to their way of working. The main weakness of the proposal was centered on ease of use since the modeling and resolution of the problem require advanced knowledge of optimization techniques.This research was funded by Universidad de La Frontera, research direction, research project DIUFRO DI22-0043
A Process Model for Continuous Public Service Improvement: Demonstrated in Local Government Context for Smart Cities.
The new era of the smart city is accompanied by Information and Communication Technology (ICT) and many other technologies to improve the quality of life for the citizen of the modern city, that in turn, has brought immense opportunities as well as challenges for government and organizations. Local authorities of the cities provide multiple services across different domains to the citizens (e.g. transport, health, environment, housing, etc.). Citizens are involved during different stages of smart city services and provide their feedback across those domains. Existing smart city initiatives provide various technological platforms for gathering citizens’ feedback to provide improved quality of services to them. Even though technological developments have resulted in a higher degree of digitalization, there is a need for improvement in the services provided by municipalities. There are multiple engagement platforms to obtain citizens’ feedback for the improvement of smart city services and to transform public services. However, limited studies consider the challenges faced by practitioners at the local level during the incorporation of those feedback for further service improvement. As a result, city services fail to fulfil the need of citizens and do not meet the goals set by existing engagement platforms. Technology-oriented solutions in the public sector domain require a logical and structured approach for the transformation of public services and digitalization. Enterprise Architecture (EA) can provide this structured approach to transform public services by providing a medium to manage change, and to respond to the need of multiple stakeholders including citizens. Thus, this research proposes a process model based on the guidelines of EA and the collaboration with practitioners that would assist local authorities to provide improved services to the citizens and fulfil their needs
A Hybrid Data-Driven Web-Based UI-UX Assessment Model
Today, a large proportion of end user information systems have their
Graphical User Interfaces (GUI) built with web-based technology (JavaScript,
CSS, and HTML). Some of these web-based systems include: Internet of Things
(IOT), Infotainment (in vehicles), Interactive Display Screens (for digital
menu boards, information kiosks, digital signage displays at bus stops or
airports, bank ATMs, etc.), and web applications/services (on smart devices).
As such, web-based UI must be evaluated in order to improve upon its ability to
perform the technical task for which it was designed. This study develops a
framework and a processes for evaluating and improving the quality of web-based
user interface (UI) as well as at a stratified level. The study develops a
comprehensive framework which is a conglomeration of algorithms such as the
multi-criteria decision making method of analytical hierarchy process (AHP) in
coefficient generation, sentiment analysis, K-means clustering algorithms and
explainable AI (XAI)
Energy Supplies in the Countries from the Visegrad Group
The purpose of this Special Issue was to collect and present research results and experiences on energy supply in the Visegrad Group countries. This research considers both macroeconomic and microeconomic aspects. It was important to determine how the V4 countries deal with energy management, how they have undergone or are undergoing energy transformation and in what direction they are heading. The articles concerned aspects of the energy balance in the V4 countries compared to the EU, including the production of renewable energy, as well as changes in its individual sectors (transport and food production). The energy efficiency of low-emission vehicles in public transport and goods deliveries are also discussed, as well as the energy efficiency of farms and energy storage facilities and the impact of the energy sector on the quality of the environment
Prioritizing the barriers to tourism growth in rural India: an integrated multi-criteria decision making (MCDM) approach
Purpose – Tourism is one of the upcoming service industry in India with high potentials for future growth, particularly in rural areas. Many potential barriers are affecting the growth of tourism in rural India. Therefore, it is essential to explore and prioritize the barriers to tourism growth in rural India. Design/methodology/approach – Qualitative and quantitative responses from “16” experts related to tourism and hospitality management from central India are collected for this study. An integrated Multi-Criteria Decision Making (MCDM) based framework is adopted to identify and relate significant barriers to tourism growth in India. Findings – The result of the study identified many significant barriers and their importance to tourism growth in rural India. Research limitations/implications – The findings of this study add to the knowledge base of tourism research in line with the previous literature. This study offers an in-depth understanding of barriers focusing on rural tourism growth and devising both the plan of action and the suggestive measures in dealing with rural tourism. Originality/value – The study provides a robust framework by integrating Interpretive Structural Modelling(ISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) to explore and prioritizing the critical barriers to rural tourism growth in India. The results of this study can help the decision-maker to fundamentally improve the economy of India through the growth of rural tourism
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