17 research outputs found

    Dynamic systems in the supply of pellets and distribution of the pellet production process

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    System archetypes are models of behavior of a system, understood as generic structures or as an overview of typical systems. There are recognized structures that show repetition in many different situations. Archetypes are depicted as appearances of common combinations through amplifying and balancing feedback loops. They are constantly used to facilitate a quick understanding of the system and their knowledge and already learned features, their insight and insight. As analytical features, they help people change their thinking for a much larger systemic perspective to understand a phenomenon or dynamic, and in some situations when real corrective action is not taken

    Modelling with Structural Equation Modelling – Application and Issues

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    Structural equation modeling (SEM) is a comprehensive statistical modeling tool for analyzing multivariate data involving complex relationships between and among variables. SEM surpasses traditional regression models by including multiple independent and dependent variables to test associated hypothesizes about relationships among observed and latent variables. SEM explain why results occur while reducing misleading results by submitting all variables in the model to measurement error or uncontrolled variation of the measured variables. SEM provides a way to test the specified set of relationships among observed and latent variables as a whole, and allow theory testing even when experiments are not possible. Structural Equation Modeling (SEM) is a powerful collection of multivariate analysis techniques, which specifies the relationships between variables through the use of two main sets of equations: Measurement equations and structural equations. Measurement equations test the accuracy of proposed measurements by assessing relationships between latent variables and their respective indicators. The structural equations drive the assessment of the hypothesized relationships between the latent variables, which allow testing the statistical hypotheses for the study. Additionally, SEM considers the modeling of interactions, nonlinearities, correlated independents, measurement error, correlated error terms, and multiple latent independents each measured by multiple indicators. In this paper will be presented application of relationship between reverse logistics and circular economy using some SEM fit indexes. The process of validating the measurement model requires testing each cluster of observed variables separately to fit the hypothesized CFA model. The statistical test uses the most popular procedures of evaluating the measurement model: Chi-square CMIN (Ο‡2), Goodness-of-Fit Index (GFI), and Percent Variance Explained

    Vehicle routing and scheduling – The traveling salesman problem

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    The classification of routing and scheduling problems depends on certain characteristics of the service delivery system, such as size of the delivery fleet, where the fleet is housed, capacities of the vehicles, and routing and scheduling objectives. In the simplest case, we begin with a set of nodes to be visited by a single vehicle. The nodes may be visited in any order, there are no precedence relationships, the travel costs between two nodes are the same regardless of the direction traveled, and there are no delivery-time restrictions. In addition, vehicle capacity is not considered. The output for the single-vehicle problem is a route or a tour where each node is visited only once and the route begins and ends at the depot node. The tour is formed with the goal of minimizing the total tour cost. This simplest case is referred to as a traveling salesman problem (TSP). An extension of the traveling salesman problem, referred to as the multiple traveling salesman problems (MTSP), occurs when a fleet of vehicles must be routed from a single depot. The goal is to generate a set of routes, one for each vehicle in the fleet. The characteristics of this problem are that a node may be assigned to only one vehicle, but a vehicle will have more than one node assigned to it. There are no restrictions on the size of the load or number of passengers a vehicle may carry. The solution to this problem will give the order in which each vehicle is to visit its assigned nodes. As in the single-vehicle case, the objective is to develop the set of minimum-cost routes, where β€œcost” may be represented by a dollar amount, distance, or travel time. If we now restrict the capacity of the multiple vehicles and couple with it the possibility of having varying demands at each node, the problem is classified as a vehicle routing problem (VRP). In this paper will be presenteds the TSP procedure for delivery and routing of new product L-carnitine from Koding – Skopje which life development is in the introduction or development phase

    Decision Making Using Sequential Equation Modelling Applied for Pellet Production

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    By means of learning experiences, students are expected to know, understand, and be able to demonstrate certain skills, behaviors, and attitudes. These learning experiences have been defined and described by several different learning theories. The 21th century the most common learning theories have been behavioral and cognitive learning theories. Behavioral learning theorists explain learning as relatively permanent change in β€œhierarchical, observable, and measurable behaviors” whereas cognitive learning theorists explain learning β€œas an internal change in mental associations”. The pellet production (PP) has the potential to improve the social, economic and environmental elements of the local community, as well as to expand the development of state economy growth. Work study examines community support for that development in the context of sustainable development. This topic is interesting for processing because it deals with specific and so far in Macedonia untreated problems and aspects arising from the relationship between the local community and the state efforts for better conditions for development and higher standard

    A methodology for closing the gap between the competences of students and recent graduates and labour market needs. The case of the Republic of North Macedonia

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    The youth unemployment is one of the most pressing problems for every economy. For addressing this issue in the Republic of North Macedonia, numerous project initiatives and activities are in the phase of planning and implementation. Part of these is the implemented project: β€˜Building capacities for better employability’. Through the project activities, it was proposed to be institutionalized the stakeholder cooperation for matching education curricula according to labour market needs. In order to increase the employability of students and graduates, the main aim which is also the goal of this study, was developing a methodology for closing the gap between the skills of students and graduates and the Labour market needs, by enhancing the entrepreneurial education dominance in high education curricula. Through advanced understanding of the entrepreneurial mind-set, new opportunities in teaching and learning can enhance the University provision. For that purpose, case studies for the best UK practices in employability were developed and a survey for investigating the needs and requirements of the Macedonian high-educational sector was conducted. The research findings comprised rich informative set of recommendations that was a base for developing the methodology for closing the skills gap. The methodology was organised in four main levels with a number of institutions (actors) and activities (measures) related to them. The application of this methodology resulted with an outline of a stakeholder plan that offers insights into other areas of study and research possibilities. The contribution of this study is twofold. It adds on the literature for high-sector education and employability, but also it has practical implications for all stakeholders responsible in coping with the unemployment issue. The proposed methodology assists in monitoring the labour market changes and addressing them with improvements in the university curricula accordingly. It could be a powerful tool in the hands of the stakeholders for better employability of the students/graduates and can facilitate whole process. Overall, it will support the Republic of North Macedonia’s future strategies at Government, University and Faculty level in their strides toward creating more skilful and employable youth

    Innovativeness in Macedonian Companies: Evidence from the Community Innovation Survey

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    The importance of innovations for development of knowledge–based economies is widely acknowledged. However, certain challenges for researching the innovativeness in post–socialist economies still exist. We analyse the most influential drivers for innovativeness in Macedonian enterprises. Based on the extended literature review and the firm–level dataset collected by the CIS 2012 (Community Innovation Survey 2012), the conceptual model for identifying the factors that drive innovation was developed and tested with standard multiple regression. The findings confirm that firm innovativeness could be improved by extending the number of collaborators and sources for information and knowledge. Also, further investments in research and development for innovation positively impact the variety of innovation activities in companies. In addition to the theoretical and practical implications, this study is significant because the proposed method could be adjusted and applied in many countries where CIS research is conducted

    Generations of innovation models and their characteristics – towards creating a new innovation model

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    Innovation is a process that consists of phases and activities and requires resources and knowledge. Innovation models define the innovation process. Innovation models are mentioned in the literature reviews with different names such as work frame, paradigm, sequence, process, etc. In this paper we give a summary of six generations of innovation models in order to show their transformation from linear models to models of open innovation. Each generation of innovation models has a specific character. Independent of the chronology and typology that has been used to separate models into generations, the focus can be put on social, educational and organizational innovation on one side, and technological innovation on the other side. We focus on the company level innovation models. The first and second generation innovation models are very simple and they are predictors of innovation models of the third generation which confirm that innovation can occur in different places throughout the process. The fourth generation focuses on product and process integration and the fifth generation models accent system integration and networking. The sixth generation of innovation models is characterized by dynamism, integration, systematic approach and a high level of interactivity

    Vehicle routing and scheduling – The traveling salesman problem

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    The classification of routing and scheduling problems depends on certain characteristics of the service delivery system, such as size of the delivery fleet, where the fleet is housed, capacities of the vehicles, and routing and scheduling objectives. In the simplest case, we begin with a set of nodes to be visited by a single vehicle. The nodes may be visited in any order, there are no precedence relationships, the travel costs between two nodes are the same regardless of the direction traveled, and there are no delivery-time restrictions. In addition, vehicle capacity is not considered. The output for the single-vehicle problem is a route or a tour where each node is visited only once and the route begins and ends at the depot node. The tour is formed with the goal of minimizing the total tour cost. This simplest case is referred to as a traveling salesman problem (TSP). An extension of the traveling salesman problem, referred to as the multiple traveling salesman problems (MTSP), occurs when a fleet of vehicles must be routed from a single depot. The goal is to generate a set of routes, one for each vehicle in the fleet

    A summary of innovation models that promote clustering

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    The literature on innovation models shows six known and widely accepted generations of innovation models on both company and economy level. Three out of six generations of innovation models explain the importance of networking and clustering. In this paper we give a summary of the generations of innovation models and show the transformation from linear to system, networking and open innovation models. The main goal is to give a framework that will be used as a foundation for creating a theoretical innovation model which should increase the company’s innovation activity by using the concept of clustering and networking as a concept for improving the country’s innovative performance. Companies can be clustered by regions (this will enable easier engagement and enrollment) and by industry (smaller and less competitive companies will be enabled to innovate) with a possibility of including government bodies and educational institutions in the process. Clusters have a certain dynamic and they need to be fit for long term adaptability within the regions, foster building trust and a continuous culture for innovation. The cluster policy also has an effect on the National Innovation System (NIS). For countries with low innovative activity as well as decreased funding and expenditures for research and development (R&D), it is of great importance that an innovation model is created which would help companies increase innovative activities, network and share not only the expenses, but knowledge and resources as well

    Анализа Π½Π° ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈΡ‚Π΅ ΠΈ ΠΌΠ΅Ρ€ΠΊΠΈΡ‚Π΅ Π·Π° Ρ€Π°Π·Π²ΠΎΡ˜ Π½Π° ΠΏΡ€Π΅Ρ‚ΠΏΡ€ΠΈΠ΅ΠΌΠ½ΠΈΡˆΡ‚Π²ΠΎΡ‚ΠΎ ΠΈ Π·Π³ΠΎΠ»Π΅ΠΌΡƒΠ²Π°ΡšΠ΅ Π½Π° вработСноста Π²ΠΎ Π Π΅ΠΏΡƒΠ±Π»ΠΈΠΊΠ° МакСдонија - со посСбСн осврт Π½Π° Ромската ΠΏΠΎΠΏΡƒΠ»Π°Ρ†ΠΈΡ˜Π°

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    Π Π°Π·Π²ΠΎΡ˜ΠΎΡ‚ Π½Π° ΠΏΡ€Π΅Ρ‚ΠΏΡ€ΠΈΠ΅ΠΌΠ½ΠΈΡˆΡ‚Π²ΠΎΡ‚ΠΎ ΠΈ ΠΏΡ€Π΅Ρ‚ΠΏΡ€ΠΈΠ΅ΠΌΠ°Ρ‡ΠΊΠ°Ρ‚Π° ΠΊΡƒΠ»Ρ‚ΡƒΡ€Π° сС почСсто сС Π°ΠΊΡ‚ΡƒΠ°Π»ΠΈΠ·ΠΈΡ€Π° ΠΈ ΠΌΠ½ΠΎΠ³Ρƒ Скономски Ρ‚Π΅ΠΎΡ€Π΅Ρ‚ΠΈΡ‡Π°Ρ€ΠΈ ΠΈ ΠΏΡ€Π°ΠΊΡ‚ΠΈΡ‡Π°Ρ€ΠΈ Π·Π° Ρ€Π°Π·Π²ΠΎΡ˜ΠΎΡ‚ Π½Π° ΠΌΠ°Π»ΠΈΡ‚Π΅ ΠΈ срСдни ΠΏΡ€Π΅Ρ‚ΠΏΡ€ΠΈΡ˜Π°Ρ‚ΠΈΡ˜Π° ΠΊΠΎΠΈ сС ΠΈΠ½ΠΎΠ²Π°Ρ‚ΠΈΠ²Π½ΠΈ ΠΈ ΠΊΠΎΠΈ ΠΊΡ€Π΅ΠΈΡ€Π°Π°Ρ‚ Π½ΠΎΠ²ΠΈ Ρ€Π°Π±ΠΎΡ‚Π½ΠΈ мСста, Π³ΠΎ Π³Π»Π΅Π΄Π°Π°Ρ‚ ΠΏΡ€Π΅Ρ‚ΠΏΡ€ΠΈΠ΅ΠΌΠ½ΠΈΡˆΡ‚Π²ΠΎΡ‚ΠΎ ΠΊΠ°ΠΊΠΎ Π΄Π²ΠΈΠ³Π°Ρ‚Π΅Π» Π½Π° Скономскиот Ρ€Π°Π·Π²ΠΎΡ˜ ΠΈ моТност Π½Π° ΠΈΠ·Π»Π΅Π· Π½Π° Скономска Ρ€Π΅Ρ†Π΅ΡΠΈΡ˜Π° ΠΈ ΠΏΠΎΠ΄ΠΎΠ±Ρ€ΡƒΠ²Π°ΡšΠ΅ Π½Π° социо-Скономската ΡΠΎΡΡ‚ΠΎΡ˜Π±Π° Π½Π° СкономскитС ΡΡƒΠ±Ρ˜Π΅ΠΊΡ‚ΠΈ/Π³Ρ€Π°Ρ“Π°Π½ΠΈΡ‚Π΅. ΠšΡ€Π΅Π°Ρ‚ΠΎΡ€ΠΈΡ‚Π΅ ΠΈ спровСдувачитС Π½Π° ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈ Π²ΠΎ Π Π΅ΠΏΡƒΠ±Π»ΠΈΠΊΠ° МакСдонија ΠΊΠ°ΠΊΠΎ Π΄Π΅Π» ΠΎΠ΄ ΠΌΠ΅Ρ€ΠΊΠΈΡ‚Π΅ Π·Π° Ρ€Π΅ΡˆΠ΅Π½ΠΈΡ˜Π° Π·Π° создавањС Π½Π° Π½ΠΎΠ²ΠΈ Ρ€Π°Π±ΠΎΡ‚Π½ΠΈ мСста ΠΈ стимулации Π·Π° Скономски раст Π³ΠΈ ΠΏΡ€ΠΎΠΌΠΎΠ²ΠΈΡ€Π°Π°Ρ‚ ΠΏΠΎΠ»ΠΈΡ‚ΠΈΠΊΠΈΡ‚Π΅ ΠΈ ΠΌΠ΅Ρ€ΠΊΠΈΡ‚Π΅ Π·Π° ΠΏΡ€Π΅Ρ‚ΠΏΡ€ΠΈΠ΅ΠΌΠ½ΠΈΡˆΡ‚Π²ΠΎ ΠΈΠ»ΠΈ Π²Ρ€Π°Π±ΠΎΡ‚ΡƒΠ²Π°ΡšΠ΅. Π’ΠΎ контСкст Π½Π° Π½Π°ΡˆΠΈΠΎΡ‚ ΠΏΡ€ΠΎΠ΅ΠΊΡ‚ ΠΈ Π°Π½Π°Π»ΠΈΠ·Π°, имајќи ја ΠΏΡ€Π΅Π΄Π²ΠΈΠ΄ спСцифичната (Π½Π΅ΠΏΠΎΠ²ΠΎΠ»Π½Π° Скономска ΠΈ ΡΠΎΡ†ΠΈΡ˜Π°Π»Π½Π°) ΡΠΈΡ‚ΡƒΠ°Ρ†ΠΈΡ˜Π° Π²ΠΎ која сС Π½Π°ΠΎΡ“Π° Ромската ΠΏΠΎΠΏΡƒΠ»Π°Ρ†ΠΈΡ˜Π° Π²ΠΎ МакСдонија, ΠΎΠ΄ ΡƒΡˆΡ‚Π΅ ΠΏΠΎΠ³ΠΎΠ»Π΅ΠΌΠΎ Π·Π½Π°Ρ‡Π΅ΡšΠ΅ сС ΠΎΠ²ΠΈΠ΅ ΠΌΠ΅Ρ€ΠΊΠΈ, инструмСнти ΠΈ активности ΠΊΠΎΠΈ ΠΌΠΎΠΆΠ°Ρ‚ Π½Π°Ρ˜ΠΏΡ€Π²ΠΈΠ½ Π΄Π° ја Π·Π³ΠΎΠ»Π΅ΠΌΠ°Ρ‚ свСсноста, Π° ΠΏΠΎΡ‚ΠΎΠ° Π΄Π° ја ΠΏΠΎΠ΄ΠΎΠ±Ρ€Π°Ρ‚ ΠΈΠ½ΠΊΠ»ΡƒΠ·ΠΈΡ˜Π°Ρ‚Π° ΠΈ социо-Скономската ΠΏΠΎΠ»ΠΎΠΆΠ±Π° Π½Π° Π ΠΎΠΌΠΈΡ‚Π΅ Π²ΠΎ Π΄Ρ€ΠΆΠ°Π²Π°Ρ‚Π°
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