RFOS - Repository of Faculty of Organizational Sciences Univ. of Belgrade
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Evaluation of agriculture-food 4.0 supply chain approaches using Fermatean probabilistic hesitant-fuzzy sets based decision making model
No full textThe benchmarking of agri-food 4.0 supply chain (Agri4SC) falls under the multiple criteria problem in supply chain visibility (SCV) and supply chain resource integration (SCRI) for improving data analytics capabilities and achieving sustainable performance (SP). It is considered a multiple criteria decision-making (MCDM) problem due to three main concerns, namely, multiple Agri4SC evaluation criteria including the SCV, SCRI and SP criteria. These criteria have relative importance and trade-offs. Despite the tremendous efforts over the last years, none of the developed Agri4SCs have met all of the essential Agri4SC evaluation criteria. Another concern raised in the evaluation and benchmarking of the Agri4SC is the uncertainty of experts. Thus, the main contribution of this research is to propose an Agri4SC benchmarking framework in SCV and SCRI for improving data analytics capabilities and achieving SP based on an extension of the proposed Fermatean probabilistic hesitant fuzzy sets (FPHFSs) and MCDM methods. The methodology process is divided into six main parts. Firstly, an Agri4SC decision matrix is formulated based on the intersection of the Agri4SC alternatives and criteria to cover multiple Agri4SC evaluation criteria issues. Secondly, novel FPHFSs are proposed along with their operational laws, score function, accuracy function, Fermatean probabilistic hesitant fuzzy average mean operator and Fermatean probabilistic hesitant fuzzy weighted average operator. The FPHFS can encompass more sophisticated and uncertain evaluation information. Thirdly, Fermatean probabilistic hesitant fuzzy weighted zero inconsistency is formulated to assign weights to the evaluation criteria. Fourthly, the Fermatean probabilistic hesitant fuzzy decision by opinion score method (FPH-FDOSM) is formulated and used to score the alternatives that were evaluated subjectively based on SCV criteria. Fifthly, the FPH-FDOSM-based multi attributive ideal-real comparative analysis (MAIRCA) scoring method with equal probabilities is proposed to score Agri4SC alternatives that were evaluated subjectively based on weighted economic, environmental and social factors. Lastly, the MAIRCA ranking method with unequal probabilities is introduced to benchmark Agri4SC alternatives that were evaluated objectively based on the weighted subcriteria of SP and the trade-offs amongst the identified criteria. The robustness and reliability of the results are tested via sensitivity analysis and Spearman's correlation coefficient
Solar PV power plant site selection using a GIS-based non-linear multi-criteria optimization technique
No full textThe ongoing rise in energy consumption imposed serious environmental challenges by using fossil fuels. The use of renewable energy sources is being increasingly explored as a potential answer for achieving sustainable energy production and minimizing adverse environmental effects. In the modern day, photovoltaic (PV) systems are viewed as a possible replacement for fossil fuels as a clean energy source. The installation of solar PV power plants requires vast land and huge investment. Therefore, it is necessary to select a suitable site to achieve maximum efficiency and low cost. A feasible location of photovoltaic (PV) system must consider certain criteria including land restrictions, access to roads, and transmission lines. This study analyzed ten factors grouped into four categories: geographic, technical, economic, and flood susceptibility criterion. The data of each factor is extracted from various governments, United Nation (UN), and non-government organizational bodies. Weights were assigned to ten factors by using a non-linear multi-criteria optimization technique called full consistency method (FUCOM). A geographic information system (GIS) software, ESRI ArcGIS pro, performs the weighted overlay analysis of the ten factors with weighted importance calculated by the above technique. A suitability map is created showing that a total of 2.02% of the country’s area is suitable for PV power plants, which are further divided into five suitability classes. The results highlight the distribution of suitable sites for the construction of solar PV power plant throughout the country. A sensitivity analysis is performed to highlight the impact of the factor on the final suitability map. These findings can promote the future widespread development and application of solar energy resources
Modelovanje i prognoza broja kvartalno aktivnih korisnika društvene mreže Facebook na svetskom nivou
No full textOd kada je kreirana prva društvena mreža, pa do sada, društvene mreže privlače veliku pažnju naučne i stručne javnosti, kao i korisnika. Popularnost određene društvene mreže se vremenom menja, i ona može rasti do po nekoliko miliona aktivnih korisnika, ali može i naglo pasti i dovesti do gašenja društvene mreže. Imajući u vidu da su društvene mreže postale jedan od ključnih kanala integrisanih marketinških komunikacija kompanija, od vitalnog je značaja proceniti broj aktivnih korisnika neke društvene mreže kako bi se donela odluka o tome da li započeti, nastaviti ili prekinuti oglašavanje na njoj. Ovaj naučni rad ima za cilj upravo to, da prikaže prognozu broja aktivnih korisnika Facebook društvene mreže u periodu od četvrtog kvartala (Q4) 2022. godine do drugog kvartala (Q2) 2024. godine, modelovanjem vremenskih serija i primenom ARIMA metodologije. Rezultati našeg ocenjenog modela vremenske serije pokazuju da će broj aktivnih korisnika ove društvene mreže rasti i dostići 3.3 milijarde korisnika do polovine 2024. godine. Ovaj naučni rad doprinosi postojećoj literaturi dvostruko. Prvo, ukazuje na to da broj korisnika društvene mreže Facebook neće opasti u narednom periodu i drugo, da se ARIMA metodologija može uspešno koristiti za modelovanje broja korisnika neke društvene mreže
The Role of Blockchain in C2C E-Commerce Business Models
No full textThis chapter analyses the role and potential applications that blockchain as a technology can bring to C2C e-commerce business models. The main goal is to present a systematic analysis of potential applications of blockchain in C2C e-commerce, presenting the expected benefits and the main challenges. As a proof-of-concept, the chapter will specifically address the aspect of developing a C2C market based on blockchain, addressing the specifics of the business model, implementation aspects, and interest of potential customers. The authors propose a design of a C2C platform based on blockchain, that enables efficient and secure C2C transactions without intermediaries. The authors also present the results of a preliminary readiness study, based on the UTAUT2 model of assessing technological readiness. The results point out the importance of the effect of social influence on behavioral intention. The results aim to help business and technical developers shape their blockchain-based e-commerce business models
Entrepreneurs’ Preferences Towards Online Market Research Packages: А Discrete Choice Analysis
No full textStartups have become a buzzword in the last couple of years, and entrepreneurship became career path for a number of people in the world. With all the advances in education and government subsidizing all over the world, still, statistics shows only a small percentage of successful startups. Studies have shown that the one the leading reasons for startup failure is the misreading of market’s needs. The aim of this paper is to determine the approach to market research, knowledge of tools and methods, and preferences towards online market research tools of entrepreneurs by using Discrete Choice Analysis. The research gathered 187 valid responses from a panel of participants working on developing new products and business, using an online survey tool. In the paper it is shown that the most important attributes for entrepreneurs are the price of the market research tool, followed by the level of details in the report generated, with more in-depth analysis regarding segmentation, simulations, and Marginal Willingness to Pay in the further chapters. The results of the research imply the need for a market research business model optimized for those starting a new business, focused primarily on detailed reporting and analysis, with the pricing model adjusted to the lack of resources entrepreneurs face at the start of their ventures, which would help them better understand the market-fit at the beginning and raise the statistic of successful startups
Morphometric and volumetric analysis of lacrimal glands in patients with thyroid eye disease
No full textAssessment of morphometric and volumetric changes in lacrimal glands in thyroid eye disease, its clinical manifestations in relation of disease progression. Retrospective volumetric analysis included both genders and was performed on total of 183 patients - 91 patients with diagnosed Grave’s disease and thyroid eye disease and 92 patients without Grave’s disease and thyroid eye disease who underwent multidetector computed tomography (MDCT) examination in routine daily work according to other medical indications. In the group of females, there was statistical significance between patients with thyroid eye disease and controls who were smoking and had body weight gain. We found statistical significance in volumetric enlargements for both orbits in both genders for the patients group when compared to controls. There was also statistical significance in morphometric characteristics for the lacrimal gland diameters measured. Determination planimetric morphometric parameters of importance were coronary height of lacrimal gland of the right eye, coronary height of lacrimal gland of the left eye and coronary width of lacrimal gland of the left eye for the group of males. In a group of females the established determination parameters of importance were the coronary height of lacrimal gland of the left eye, the axial width of lacrimal gland of the left eye, volume of lacrimal gland of the right eye and the volume of lacrimal gland of the left eye. When we compared the displaced lacrimal gland coming forward (proptosis) in time progressing disease between group of patients and controls, we also found statistical significant connection. Evaluation of lacrimal gland volumetric and morphometric data may increase validity of defining this anatomical substrate and its morphology disruption as liable tool for thyroid eye disease progression follow up and treatment planning and outcome
An Approach to Corporate Credit Rating Prediction Using Computational Intelligence-Based Methods
No full textCredit ratings tend to be very informative for investors and issuers and might serve as a powerful tool. The purpose of this paper is to investigate existing credit rating methodologies (e.g. Moody's, Standard and Poor's, Fitch) and to introduce improved data model for corporate ratings prediction based on computational intelligence methods. We hope that this study will provide academic researchers and industry practitioners new insights into the aspects of credit rating and its predictions. The research is performed on the selected companies that are constituents of the S&P 500 index. Company data from financial reports over period of 2016 to 2019 are analyzed and numerous financial indicators are included into analysis. The paper focuses on the design of data model, data preparation and working with missing values. Various well-known imputation techniques but also computational intelligence-based ones (e.g. fuzzy C-means) are applied to handle missing values and improve performance. In further research, the corporate credit rating prediction is brought down to a classification problem. Being a successful computational intelligence technique for credit ratings prediction, a typical neural network model is applied and compared to support vector machines as another popular data-based method in this domain. Finally, we have performed both cross-industry and industry-specific analysis. It is shown that industry-specific approach improved prediction results achieved by cross-industry data
Prioritization of unmanned aerial vehicles in transportation systems using the integrated stratified fuzzy rough decision-making approach with the hamacher operator
No full textThe Integration of Unmanned Aerial Vehicles (UAVs) into transportation systems has numerous benefits, ranging from the ability to record real-time data to having high mobil-ity and broad vision. Because of the increasing levels of congestion in the cities, many of the transportation system tasks, such as traffic management and data collection, have become complicated to handle. The implementation of UAVs in transportation systems is a feasible solution to overcoming these problems. Therefore, UAVs have become a point of interest for many transportation system authorities. This study aims to introduce an integrated Fuzzy Level Based Weight Assessment (LBWA) in a stratification environment (SF-LBWA) and Fuzzy Rough Hamacher Combined Compromise Solution (CoCoSo) model to resolve the prioritization of Unmanned Aerial Vehicles in transportation system problems. The decision framework for such a problem is defined by establishing the relevant alternatives and criteria according to the specialized literature. Hence, a case study illustrates the for-mulation and solution of the problem. This study will indicate the most suitable alternative for the problem and provide guidance as authorities look for ways to integrate UAVs and transportation systems
Changing criteria weights to achieve fair VIKOR ranking: a postprocessing reranking approach
No full textRanking is a prerequisite for making decisions, and therefore it is a very responsible and frequently applied activity. This study considers fairness issues in a multi-criteria decision-making (MCDM) method called VIKOR (in Serbian language-VIsekriterijumska optimizacija i KOmpromisno Resenje, which means Multiple Criteria Optimization and Compromise Solution). The method is specific because of its original property to search for the first-ranked compromise solutions based on the parameter v. The VIKOR method was modified in this paper to rank all the alternatives and find compromise solutions for each rank. Then, the obtained ranks were used to satisfy fairness constraints (i.e., the desired level of disparate impact) by criteria weights optimization. We built three types of mathematical models depending on decision makers' (DMs') preferences regarding the definition of the compromise parameter v. Metaheuristic optimization algorithms were explored in order to minimize the differences in VIKOR ranking prior to and after optimization. The proposed postprocessing reranking approach ensures fair ranking (i.e., the ranking without discrimination). The conducted experiments involve three real-life datasets of different sizes, well-known in the literature. The comparisons of the results with popular fair ranking algorithms include a comparative examination of several rank-based metrics intended to measure accuracy and fairness that indicate a high-quality competence of the suggested approach. The most significant contributions include developing automated and adaptive optimization procedures with the possibility of further adjustments following DMs' preferences and matching fairness metrics with traditional MCDM goals in a comprehensive full VIKOR ranking
The appropriation of blockchain implementation in the supply chain of SMES based on fuzzy LMAW
No full textThis study investigates the adoption of blockchain technology in small and medium-sized enterprises’ (SMEs) supply chains. Blockchain has been deemed a “Game Changer” for its potential benefits but also has several limitations due to its properties and SMEs’ limited resources. Small and medium-sized companies (SMEs) have more problems employing Industry 4.0 Technologies in practice than larger companies. So, the employment of BC in SMEs’ supply chains, as the economy's backbone, deserves a full investigation which has been addressed in this paper. We use the Technology–Organization–Environment framework to examine both positive and negative factors affecting blockchain adoption in SMEs. A Delphi method was used to refine a list of 42 factors down to the 22 most essential ones. These factors were then prioritized using the Fuzzy Logarithmic Additive Weights Methodology based on expert preferences. The findings indicate that while financial factors play a crucial role in adoption, transparency, and traceability are significant benefits that motivate organizations to adopt blockchain. The organizational dimension also has a substantial impact on decision-making. In this study, we conclude that SMEs must carefully consider their circumstances before adopting blockchain technology, given its infancy state. The barriers to adoption are just as significant as incentives, and SMEs must weigh the financial and organizational factors before making the decision. This study extends the literature by comprehensively looking at all possible factors influencing BC adoption by SMEs. Furthermore, we have highlighted valuable insights for policymakers and SME owners to make the best decision