RFOS - Repository of Faculty of Organizational Sciences Univ. of Belgrade
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Certification to compensate gender prejudice - Analysis on impact of management system certification on export
No full textManagement system certification signals that the organization meets international standards, which provides a certain confidence in the company. This confidence is in particular needed for exporting companies in developing countries. Because the business world is dominated by men, female leadership might be another reason to have less confidence in a company. Women-led companies may therefore benefit more from certification. Therefore, this study empirically tests the impact of certification on export, and the moderating effect of female leadership. We use data from enterprise surveys conducted by the World Bank in 2013 that include 4111 firms from 25 Central and Eastern European countries in transition. We implement a recursive bivariate probit model and an extensive sensitivity analysis to account for endogeneity issues. Results confirm that certification and export are positively correlated. Firms managed by females benefit more from certification based on international standards than firms managed by men, especially in the service sector. This suggests that certification compensates for the possibly negative connotations of female leadership. Female managers may consider implementing a management system and get it certified, resulting in a competitive advantage in export markets. Our findings provide food for thought for purchase managers - are they free from prejudice
Selection of the optimal medical waste incineration facility location: A challenge of medical waste risk management
No full textUvod/Cilj. Među izazovima 21. veka, medicinski otpad (MO) je, imajući u vidu povećanje njegove količine, raznovrsnost i kompleksnost, postao rastući problem kako za životnu sredinu, tako i za ljude. Zbog toga je upravljanje MO postalo jedan od veoma važnih ekoloških imperativa. Srbija nema potencijala za adekvatno odlaganje celokupnog MO i mora da ga izvozi u zemlje koje imaju postrojenja za njegovo spaljivanje. Spaljivanje MO smanjuje moguće rizike prouzrokovane njegovim neodgovarajućim odlaganjem kao i emisije zagađivača životne sredine, ali rezultira potrebom za "pametnim" izborom lokacije za postrojenja za spaljivanje da bi bili ispunjeni različiti ekološki, ekonomski i tehnički kriterijumi. Metode. Za izbor optimalne lokacije postrojenja za spaljivanje MO korišćeni su sledeći kriterijumi: količina MO koja mora da se transportuje, vreme transporta između lokacija, trenutno zagađenje lokacije, stopa nezaposlenosti i bezbednost lokacije u odnosu na njenu izloženost prirodnim nepogodama i nesrećama. Korišćenjem rezultata za sedam efikasnih lokacija dobijenih metodom Data Envelopment Analysis (DEA), upotrebili smo model ciljnog programiranja za dalju analizu izbora najpogodnije lokacije za postrojenje za spaljivanja MO. Rezultati. Primenom metode DEA za izabrani scenario i analize kriterijuma relevantnih za izbor najpogodnije lokacije, nađeno je sedam efikasnih lokacija za postrojenje za spaljivanje MO. Optimalna lokacija je bila lokacija 13. Zaključak. Na osnovu dobijenih rezultata, pokazali smo da je primenom ciljnog programiranja moguće razviti metodologiju za selekciju optimalne lokacije za postrojenje za spaljivanje MO, kao jedne od neophodnih aktivnosti za upravljanje rizikom od MO.Background/Aim. Among the other challenges of the 21st century, medical waste (MW) has become an arising problem for both the environment and people because of its increasing amount, variety, and complexity. That is way MW management has become one of the very important ecological imperatives. Serbia with no potential for appropriate disposal of all MW is forced to export MW to countries with MW incineration facilities. Incineration lowers the possible risks of inappropriate disposal and the emission of environmental pollutants, but leads to the need for a "clever" choice of the incinerator facility location which has to meet diverse environmental, economic and technical criteria Methods. The criteria for the choice of optimal locations for a MW incinerator facility were as follows: the amount of MW that needs to be transported, the transport time from other locations, the current pollution of the location, the unemployment rate and the location safety in terms of natural disasters and accidents. By using the obtained results for seven efficient locations gained by Data Envelopment Analysis (DEA), we used a goal programming for the analysis of the most suitable location for a MW incineration facility. Results. In the proposed methodology on the chosen scenario and analysing the criteria relevant for selecting the most suitable location, using the DEA method, seven efficient locations for MW incineration facility were obtained. The optimal location was location 13. Conclusion. Based on the obtained results, we demonstrated that by the use of goal programming it is possible to develop a methodology for selection of optimal MW incineration facility location as one of the necessary activities of MW risk management
E-function for Fuzzy Clustering in Complex Networks
No full textIn many real-life situations, data consists of entities and the connections between them, which are naturally described by a complex network (graph). The structure of the network is often such that it is possible to group nodes based on the existence of connections between them, where such groups are called clusters (communities, modules). If the nodes are allowed to partially belong to clusters, they are called fuzzy (overlapping) clusters. There is a huge number of algorithms in the literature that perform fuzzy clustering, so a mechanism is needed to evaluate such clustering. The function that assesses the quality of a performed clustering is called the cluster quality function. One of the latest proposed quality functions is the E-function. The E-function is based on a comparison of the internal structure of a cluster, i.e., the connection between nodes within a cluster and the connection of its nodes with the nodes of other clusters. Due to its exponential nature, the E-function is sensitive to small changes in the membership degrees to which the nodes belong to clusters. As such, it has shown good results in evaluating clustering on known data sets. In this paper, the experimental results that the modified E-function achieves in the case of overlapping clusters are presented. Also, some possibilities for fuzzy clustering by optimizing the E-function are displayed
A methodological framework for the integration of machine learning algorithms into agent-based simulation
No full textTraditionally, agent-based modelling and simulation relied on using utility function in agents??? decision-making process. Some drawbacks in this process are identified, and a potential remedy to the issue is proposed. This paper introduces a methodological framework for building a hybrid agent-based model that aims to overcome some of the elaborated problems related to the usage of a utility function. In the proposed approach, a machine learning algorithm substitutes the utility function, thus providing a possibility to use various algorithms. The proposed methodological framework has been applied to a case study of churn in a telecommunications company. Three models have been created and used for simulation experiments, two using the proposed methodology and one using utility function. The pros and cons of different approaches are identified and discussed
Development of the Waste Management Composite Index Using DEA Method as Circular Economy Indicator: The Case of European Union Countries
No full textThis paper aims to develop a Waste Management Composite Index (WMCI) as a Circular Economy (CE) indicator by using a DEA-based model. This approach will enable making a mutual comparison, i.e. comparative analysis of the countries CE performances. Even though many countries have already accomplished a great deal in terms of the CE, there are still numerous of those that have not progressed much, finding themselves at the very beginning of the process. For that matter, the development of the indicators would help monitor changes during the transition process and while shifting to the CE model. In this paper, a tailor-made DEA model is created to fit a two-layer composite index WMCI comprising of eight relevant sub-indicators. The model is applied for the comparison of the 26 European Union (EU) countries. The obtained results could help maintain the countries informed about their position on the ranking list, alongside the level of their implementation of the CE with guidelines and recommendations for possible future development in this area
A novel business context-based approach for improved standards-based systems integration-a feasibility study
No full textSystems integration processes need to become more efficient and effective in order to allow enterprises to be nimbler and more responsive in today's dynamic markets. Systems integration typically depends on data exchange standards (DESes) and the associated DES usage specification that provides precise standard implementation requirements. However, there are significant inefficiencies in DES usage specification management today. Therefore, to achieve the objective of more responsive enterprises, DES usage specification management, particularly reuse, needs to advance. The Core Component Technical Specification carries the promise to advance the reuse by introducing the notions of Core Components (CCs), as DES building blocks, and Business Information Entities (BIEs), as DES usage specification. While the CCs idea has been successfully implemented in industry DES, the BIEs idea has been implemented only in a basic form, falling short of enabling the BIE reuse to its full potential. To realize the full potential of the BIE reuse, BIE development in industry standard usage needs to utilize the notion of business context better. In this paper, we reviewed existing business context models including UN/CEFACT Context Model (UCM), Enhanced UCM (E-UCM), and Business Context Ontology (BCOnt) and found that they were promising tools to improve the effectiveness of the BIE development and reuse. In addition to that contribution, this research took a closer look at E-UCM in particular. Two novel assessment criteria called expressiveness and effectiveness were defined. Using an industry use case and the two assessments, we showed short-comings of E-UCM such as semantic ambiguity and business rule disconnection. From there, improvements were outlined for future work to device them into E-UCM to enable a more efficient and effective BIE development and reuse process
EXPLODE - a new model of exploratory learning environment for neural networks to improve learning outcomes
No full textThe paper proposes EXPLODE, a new model of exploratory learning environment for teaching and learning neural networks. The EXPLODE model is about pedagogically instrumenting a software development environment to transform it into an exploratory learning environment for neural networks. Such an environment is particularly aimed for students who are skilled in programming and meets typical challenges in teaching and learning neural networks, related to the lack of prerequisite knowledge in mathematics. By providing such students with a familiar learning environment and allowing them to programmatically experiment with neural networks, the EXPLODE model aims at improving the students' learning outcomes and learning experience. The effectiveness of the model was evaluated in an experimental study with 77 final-year IT students. The results have shown that the students from the experimental group, that is, those who were exposed to the EXPLODE model, scored higher on the knowledge test. Furthermore, the perceived learning experience of the experimental group was better than that of the control group. The results have also suggested that the proposed model helps students better understand learning topics that require practical experience and facilitates a deeper understanding of the internal operations of neural networks
Production processes modelling within digital product manufacturing in the context of Industry 4.0
No full textIndustry 4.0 aims to establish highly flexible production, enabling effective and efficient mass customisation of products. Modelling techniques and simulation of production processes are among the core techniques of the manufacturing industry that facilitate flexibility and automation of a shop floor in the era of Industry 4.0. In this paper, we present an approach to support production process modelling and process model management. The approach is based on Model-Driven (MD) principles and comprises a Domain-Specific Modelling Language (DSML) named Multi-Level Production Process Modelling Language (MultiProLan). MultiProLan uses a set of concepts to specify production process models suitable for automatic instruction generation and execution of the instructions in a simulation or on a shop floor. By using MultiProLan, process designers may create process models independent of the specific production system. Such process models can either be automatically enriched by matching and scheduling algorithms or manually enriched by a process designer via MultiProLan's modelling tool. In this paper, we also present an application of our approach in the assembly industry to showcase its dynamic resource management, generation of production documentation, error handling and process monitoring
An integrated SEM-ANN approach for predicting QMS achievements in Industry 4.0
No full textIndustry 4.0 brings a revolution in using information and communication technologies within business activities. As such, Industry 4.0 enables important space for quality-related improvements but requires a sustained quality management system (QMS). The aim of this study is to predict the influence of ISO 9004:2018 QMS elements on Improvement, Learning, and Innovation achievements in Industry 4.0 using the SEM-ANN approach. The survey included 345 domestic and international companies of different types operating in Serbia. Conclusions demonstrate a direct positive influence between observed constructs (Leadership, Process Management, Resource Management, Performance Management) and Improvement, Learning, and Innovation. Only the Context and Identity of the organisation has a negative direction drawn from SEM analysis. Further, ANN verified SEM results, pointing out that all observed variables are seen as predictors of Improvement, Learning, and Innovation. The importance level corresponds to those elements' SEM ranking. The paper could provide a roadmap towards achieving sustainable results in quality improvement, learning, and innovation in Industry 4.0 era
Exploring the Key Factors of Process Improvement that Drive Competitive Advantage: A Case of Serbia
No full textThe aim of this study is to define the set of BPI factors that contribute the most to the success of gaining competitive advantage in the company. This paper aims to investigate the linkages between BPI in context of BPM and competitive advantage, and whether BPI practices ensure that companies can accomplish desired results. Structural equation modeling (SEM) was conducted to identify key factors that contribute to the success of BPI, which in turn drives competitive advantage on the market. An online survey was conducted and data has been collected from the Serbian companies from different sectors. The results highlight the impact BPI has on competitive advantage in companies and shows which factors significantly contribute to success of BPI in context of leadership and employees. To achieve desired results, the focus has to be on strong support of the leadership and good communication between employees. The study highlights significance of setting short- and long-term objectives, so that employees can understand the need for BPI projects, as well as their position in them. This study can help practitioners to be more successful in achieving BPI goals, to understand the nature of process improvement and to transform their process knowledge into competitive advantage