This thesis deals with specialized information systems for internet service providers. The aim of thesis is to compare specific information system of company Dupeto s.r.o. with an-other external systems. The first part of the thesis deals with the theoretical foundations, which is followed by the analysis of a market of this systems. After making choice of which systems are the propriet ones, the thesis gives a detailed description of these sys-tems. In conclusion there is a recommendation for Dupeto s.r.o. which system is the best for this company. This recommendation was achieved by the means of a multi-criteria de-cision making. This thesis is so helpful mainly for this company but it is helpful for other internet service providers too because it contains the analysis of the systems from various point of views.

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The assessment of the environmental and social impact of companies could be a key lever towards amore sustainable society. The aim of this report is to develop a quantitative approach based onmulti-criteria decision-making methods for organizations to conduct a corporate social responsibility materiality analysis. Through a literature review, a knowledge gap was identified on practical methods to implement a materiality analysis that meet non-financial reporting requirements.Therefore, the features of such a method were identified and a method combining analytic hierarchy process and failure modes and effects analysis was offered. The method was then used within a company in order to illustrate how the method should be applied in practice and to assess its application. The analytic hierarchy process was used to determine the relative weights of three criteria: risk, opportunity and influence on stakeholders’ assessments & decisions. Assessment scales were created for three failure modes and effects analysis indices for the criteria of risk and opportunity: severity, occurrence and control. A unique value can then be calculated for each corporate social responsibility issue in order to identify the material ones. The application of the methodology to a company underlined a few critical factors to be further investigated, in particular the quantification of the scales used for assessment and the selection of stakeholders. / Bedömningen av företagens miljöpåverkan och sociala effekter kan vara en nyckelhävarm mot ett hållbart samhälle. Syftet med denna artikel är att utveckla ett kvantitativt tillvägagångssätt baserat på beslutsfattningsmetoder med flera kriterier för organisationer att utföra en väsentlighetsanalys av företagets sociala ansvar. Genom en litteraturöversikt identifierades kunskapsgap om praktiska metoder för att genomföra en väsentlighetsanalys som uppfyller icke-finansiella rapporteringskrav. Därför identifierades funktionerna i en sådan metod och en metod som kombinerar analytisk hierarkiprocess och feleffektsanalys erbjuds. Metoden användes sedan inom ett företag för att illustrera hur metoden bör tillämpas i praktiken och för att bedöma dess tillämpning. Den analytiska hierarkiprocessen användes för att bestämma de relativa vikterna för tre kriterier: risk, möjlighet och inflytande på intressenternas bedömningar och beslut. Utvärderingsskalor skapades för tre feleffektsanalysindex för kriterierna för risk och möjlighet: allvarlighetsgrad, förekomst och kontroll. Ett unikt värde kan sedan beräknas för varje företags sociala ansvar för att identifiera de materiella.Tillämpningen av metodologin på ett företag underströk några kritiska faktorer som ska undersökas ytterligare, särskilt kvantifieringen av skalorna som används för bedömning och urvalet av intressenter.

[pt] A ascensão do desenvolvimento sustentável como um campo de pesquisa aplicada tem sido observada em várias disciplinas. No âmbito da Agenda 2030 das Nações Unidas, o cumprimento dos 17 Objetivos de Desenvolvimento Sustentável (ODS) exige a tomada de decisões considerando vários critérios geralmente complexos e conflitantes. Os métodos multicritério de apoio à decisão (MCDM) têm sido amplamente empregados em uma vasta gama de campos e disciplinas, incluindo a análise de decisão multicritério sobre questões de desenvolvimento sustentável. Mapear e analisar sistematicamente a evolução do campo de pesquisa cobrindo aplicações de métodos multicritério de apoio à decisão para o desenvolvimento sustentável nas últimas duas décadas pode ajudar governos e organizações nas transições sociotécnicas em direção à sustentabilidade. Assim, métodos MCDM para o desenvolvimento sustentável está emergindo como um domínio de estudo recente nos campos de gestão e políticas públicas. Esta dissertação tem como objetivo identificar e visualizar caminhos evolutivos e construir um roteiro científico com foco neste campo de pesquisa. Uma análise bibliométrica foi conduzida para avaliar todos os documentos revisados por pares recuperados do banco de dados Web of Science (WoS), cobrindo este campo no período de 2000-2020. A partir dos dados analisados dos artigos mais citados de um total de 3.473 documentos inicialmente recuperados, foi possível identificar e visualizar o mapa longitudinal da ciência de um campo de pesquisa em foco. As implicações para políticas contínuas e consistentes e pesquisas futuras são discutidas. / [en] The rise of sustainable development as a field of applied research has been observed across various disciplines. Within the UN 2030 Agenda scope, the achievement of 17 Sustainable Development Goals (SDGs) requires decision-making considering multiple decision criteria usually complex and in conflict. Multiple criteria decision-making methods (MCDM) have been widely employed in a wide range of fields and disciplines, including multicriteria decision analysis concerning sustainable development issues. Mapping and systemically analyzing the evolution of the research field covering applications of multicriteria decision-making methods for sustainable development in the last two decades can help governments and organizations in sociotechnical transitions towards sustainability. Thus, MCDM methods for sustainable development is emerging as a recent research domain within management and public policy fields. This dissertation aims to identify and visualize evolutionary pathways and build a scientific roadmap focusing on this research field. A bibliometric analysis was conducted to assess all peer-reviewed documents retrieved from the Web of Science (WoS) database, covering this field over the 2000-2020 timeframe. Based on the analyzed data of the most cited articles from a total of 3,473 initially retrieved documents, it was possible to identify and visualize a focused research field s longitudinal science map. The implications for ongoing, consistent policy and future research are discussed.

[pt] Na perspectiva de estimular o aprimoramento do processo de gestão da inovação pelas micro, pequenas e médias empresas (MPMEs) brasileiras e contribuir para formulação ou revisão de políticas públicas de Ciência, Tecnologia e Inovação (CTeI) voltadas para esse segmento, a presente dissertação tem como objetivo geral propor um modelo para monitorar e avaliar a capacidade inovativa de MPMEs. A pesquisa pode ser considerada descritiva, metodológica e aplicada. A partir dos resultados da revisão bibliográfica e documental sobre os temas centrais da pesquisa, desenvolveu-se um modelo para mensuração e avaliação da capacidade inovativa de MPMEs, com base na integração de dois métodos multicritério fuzzy de apoio à decisão – Fuzzy Analytical Hierarchy Process (FAHP) e Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). Visando demonstrar a aplicabilidade desse modelo no contexto das MPMEs e explicitar seus diferenciais metodológicos em comparação a outros métodos de apoio à decisão, não combinados com a teoria de conjuntos fuzzy, realizou-se um estudo junto a 15 MPMEs participantes do Programa NAGI da PUC-Rio. Destacam-se como principais contribuições da pesquisa um modelo para mensuração e avaliação da capacidade inovativa de MPMEs, que considera a complexidade, subjetividade e incerteza como características inerentes a essa atividade, e um conjunto de indicadores compostos associados às três dimensões de capacidade inovativa contempladas no modelo proposto. / [en] From the perspective of stimulating the improvement of the process of innovation management by micro, small and medium enterprises (MSMEs) and contributing to the formulation or review of public policies concerning the area of Science, Technology and Innovation (CTandI), focusing on this segment, the aim of the dissertation is to propose a model to monitor and evaluate the innovative capacity of MSMEs. This research can be classified as descriptive, methodological and applied. From the bibliographic and documentary review on the central themes of the research, a model was developed to measure and evaluate the innovative capacity of MSMEs based on the integration of two fuzzy multi-criteria methods of decision support - Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). Aiming to demonstrate the applicability of this model in the context of MSMEs and to explicit its methodological differentials in comparison to other methods for measuring the innovative capacity of enterprises, an empirical study with 15 MSMEs participants of the NAGI Program at PUC-Rio was carried out during the applied phase of this research. The main contributions are a model for measuring and evaluating the innovative capacity of MSMEs, which considers the complexity, subjectivity, and uncertainty as characteristics inherent to these activities, and a set of composed indicators associated with the three dimensions of the innovative capacity considered in the proposed model.

In cities all over the globe, bicycle-sharing systems are being implemented as a way of promoting bicycling as the primary mode of transportation. Cities encourage the residents to bicycle as a way of improving local environments and reducing traffic congestion. A step in this direction is providing a bicycle-sharing system, which increases the accessibility and mobility in a city. For the availability of a bicycle-sharing system to be maximized, the locations of the docking stations must be carefully selected and analyzed. Several studies have been conducted where the availability of bicycle-sharing systems have been evaluated, using different approaches. However, no studies have been conducted in Stockholm on the newly established Stockholm eBikes bicycle-sharing system. Thus, this thesis aims to evaluate the location of bicycle-sharing stations and determine the most suitable locations of those in Stockholm. This is done through a GIS-based MCDM method which applies an Analytical Hierarchy Process to weigh the criteria that must be considered. The analysis is done in QGIS, an open-source GIS-software, with data from OpenStreetMap and local data sources. The results indicate that the suitability of the current bicycle-sharing stations in Stockholm is high considering the analyzed criteria. Further, a suggestion is given for locations where the suitability for bicycle-sharing stations is high. This suggestion proposes new locations in Stockholm where a bicycle- sharing station could increase the availability of the bicycle-sharing system as well as the mobility in the city.

<p dir="ltr">Highway safety continues to pose a serious challenge to the social sustainability of transportation systems, and initiatives are being pursued at all levels of government to reduce the high fatality count of 42,000. At the same time, it is sought to ensure higher travel efficiency in order to increase economic productivity. The emergence of automated transportation provides great promise to mitigate these ills of the transportation sector that have persisted for so many decades. With regards to safety, such promise is rooted in the capability of autonomous vehicles to self-drive some or all of the time, thus reducing the impact of inherently errant human driving to which 95% of all crashes have been attributed. With regards to mobility, such promise is guided by the capability of the autonomous vehicle to carry out path planning, navigation, and vehicle controls in ways that are far more efficient than the human brain, thereby facilitating mobility and reducing congestion-related issues such as delay, emissions, driver frustration, and so on.</p><p dir="ltr">Unfortunately, the two key outcomes (safety and mobility) are reciprocal in the sense that navigation solutions that enhance safety generally tend to reduce mobility, and vice versa. As such, there is a need to assign values explicit to these performance criteria in order to develop balanced solutions for AV decisions. Most existing machine-learning-based path planning algorithms derive these weights using a learning approach. Unfortunately, the stability of these weights across time, individuals, and trip types, is not guaranteed. It is necessary to develop weights and processes that are trip situation-specific. Secondly, user trust in automation remains a key issue, given the relatively recent emergence of this technology and a few highly-publicized crashes, which has led to reservations among potential users.</p><p dir="ltr">To address these research questions, this thesis identifies various situational contexts of the problem, identifies the alternatives (the viable trajectories by fitting curves between the vehicle maneuver’s initial and final positions), develops the decision criteria (safety, mobility, comfort), carries out weighting of the criteria to reflect their relative significance, and scales the criteria to develop dimensionless equivalents of their raw values. Finally, a process for amalgamating the overall impacts of each driving decision alternative is developed based on the weighted and scaled criteria, to identify the best decision (optimal trajectory path). This multi-criteria decision making (MCDM) problem involves the collection of data through questionnaire surveys.</p><p dir="ltr">The weights obtained early in the MCDM process could be integrated into any one of two types of planning algorithms. First, they could be incorporated into interpolating curve-based planning algorithms, to identify the optimal trajectory based on human preferences. Additionally, they can be integrated into optimization-based planning algorithms to allocate weights to the various functions used.</p><p dir="ltr">Overall, this research aims to align the behavior of autonomous vehicles closely with human-driven vehicles, serving two primary purposes: first, facilitating their seamless coexistence on mixed-traffic roads and second, enhancing public acceptance of autonomous vehicles.</p>

Providing products that are customized to meet a specific customer's unique needs is challenging for companies. Product configuration systems are tools that enables parts of these activities to be performed automatically. However, there is a lack of systems designed to ensure that the configured products are based on customer needs. Decision support systems based on Multi-criteria decision making methods have the potential to solve this problem. Yet, there is a lack of knowledge regarding various multi-criteria decision making methods. Moreover, there is a need to reduce the complexity of the methods by incorporating them into user-friendly software’s. This research therefore investigates how the architecture of a decision support system based on multi-criteria decision making methods could be structured to include customer needs and suggest product configurations based on them. Through a literature review various methods are analyzed. In collaboration with an aircraft towing tractor manufacturer as a representative of customizable products the architecture of the system is developed. The study shows that a system based on a combination of Analytical Hierarchy Process, Quality Function Deployment and Expert system can solve the problem. This is to the authors knowledge the first study to use this combination. It provides an approach of how to ensure that product configurations can be aligned with customer needs and that the consistency of these needs is assured.

Yes / Increasing reliance on digital technologies has led to a significant shift in how businesses operate, with many now relying heavily on digital platforms for effective planning, communication, sales, marketing, supply chain, and logistics management. In this context, knowledge sharing platforms enable academic–industry collaboration in which exchange of ideas, opinions, experience, and expertise brings collective intelligence in cooperative learning ecosystem thereby expediting decision making. However, establishing long-term commitment among the partners, allocation of time and resources for sharing tacit knowledge, collaboration among partners with different strategic priorities, and real-time knowledge sharing capabilities are essential for effective and rapid learning in knowledge sharing platforms. The present article will examine these benefits and challenges in knowledge sharing and its impact on supplier selection platforms in Asian automakers. The findings of this article will be helpful for researchers and practitioners intending to explore the role of cooperation in knowledge sharing and digital transformation amid competitive environment prevalent in the automotive industry. The potential supplier database is first examined for qualifying the capability requirements put forth in this article and further prioritized using a multicriteria decision-making technique and analytic hierarchy process. The article results reveal that the manufacturer has highly prioritized firms’ financial transparency for supplier evaluation followed by the suppliers’ cost control, quality control, and manufacturing capabilities. The article has significant theoretical and practical implications for developing robust supplier evaluation criteria for automobile industry and a digital ecosystem for original equipment manufacturers in making supplier related decisions.

This thesis investigates the regulatory impact of the EU ETS and CBAM regulations on supplier selection processes for procuring iron ore pellets, lime, and ferromanganese from 2025 to 2035. The study is set within the context of evolving EU environmental regulations, emphasizing the importance of understanding their effects on procurement practices in the steel industry. Employing quantitative multi-criteria decision-making (MCDM) through a TOPSIS analysis, the study evaluates suppliers over the specified timeframe based on market price, emissions, shipping cost, and regulatory cost. Additionally, a comprehensive review of current literature within the research area is provided. The methodology section details the research approach, design, data collection, and research quality. A case study conducted at H2 Green Steel, including company background and project execution, is also outlined. The results indicate potential changes over time due to the regulatory effects of the EU ETS and CBAM, with a sensitivity analysis exploring various weight scenarios of TOPSIS results to understand the relationship between the selected criteria. The analysis highlights advantages in integrating sustainability into procurement practices, driven by regulatory incentives. These findings suggest significant implications for procurement managers, emphasizing the importance of considering regulatory costs in supplier selection and adopting long-term monitoring of regulatory changes in the EU ETS and CBAM regulations. The study's implications are discussed in terms of validity, reliability, practical application, and future research directions.