RFOS - Repository of Faculty of Organizational Sciences Univ. of Belgrade
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Adaptive fuzzy system for algorithmic trading : interpolative Boolean approach
No full textTema ovog rada je adaptivni fazi sistem za algoritamsko trgovanje. Sistem je razvijen korišćenjem interpolativnog Bulovog pristupa fazi modelovanju, analizi podataka i upravljanju. Predloženi pristup uključuje interpolativne logičke modele za fazi prepoznavanje cenovnih obrazaca na tržištu, logički DuPont metod za automatizovanu analizu profitabilnosti preduzeća, interpolativni fazi kontroler za upravljanje trgovanjem i genetski algoritam za obučavanje interpolativnog fazi kontrolera radi otkrivanja strategija. Interpolativni Bulov pristup, zasnovan na interpolativnoj Bulovoj algebri, prevazilazi problem nekonzistentnosti fazi logike. Konstruisani adaptivni fazi sistem može samostalno, iz podataka, da otkrije uspešne strategije, primeni ih za algoritamsko trgovanje i adaptira u slučaju pada njihovih performansi. Uspešnost sistema testirana je na podacima sa američkog tržišta akcija, međunarodnog deviznog tržišta i tržišta kriptovaluta.The topic of this thesis is adaptive fuzzy system for algorithmic trading. The system is developed using interpolative Boolean approach for fuzzy modeling, data analysis and control. The proposed approach includes interpolative logical models for fuzzy recognition of price patterns in market data, logical DuPont method for automated analysis of company’s profitability, interpolative fuzzy controller for trading and a genetic algorithm for extracting trading strategies by training interpolative fuzzy controller. Interpolative Boolean approach, based on interpolative Boolean agebra, solves the problem of fuzzy logic’s inconsistency with Boolean axioms. The proposed system can independently discover successful trading strategies from data, apply them for algorithmic trading and adapt in the case of performance deterioration. The system was tested on historical data from US equity, foreign exchange market and cryptocurrency market
Adaptive E-Business Continuity Management: Evidence from the Financial Sector
No full textThis paper focuses on business continuity management in organizations that use modern e-business technologies: the Internet, mobile computing, e -services, and virtual infrastructure. The aim is to make the shift from traditional Business Continuity Management (BCM) towards "e-Business Continuity Management" (e-BCM) suitable for modern technological environments. We have defined a comprehensive framework for the implementation of an adaptive e-BCM adjustable to changes in the business environment. The framework consists of practical steps for defining elements of a business continuity management system: business impact analysis, risk assessment, and a business continuity plan. We have implemented and evaluated the framework within three financial organizations. The key finding is that Business Impact Analysis and the continual improvement of the Business Continuity Management System are the driving factors for the effective establishment of an adaptive e-BCM. The proposed framework is general, and can be applied to any organization that uses modern e -business technologies
Can process and lean thinking optimize order picking performance?
No full textCertain managerial tools, i.e. process thinking and lean methodology could have a significant impact on warehousing operations, but they are largely neglected among the scholars. Thus, the purpose of this paper is to establish the extent to which managing processes, rather than functions and units, as technology based innovation initiatives monitored by lean approach, impacts the improvement of picking performance. In this case, a realistic experiment was conducted in a company that adopted process and lean way of thinking in replacing RF scanning with voice technology. For the purpose of the research, apart from the data collected from the company, six participants were employed for the experiment. The results suggest that process innovation monitored by lean in adopting voice technology optimized order picking performance, leading to better efficiency, productivity and accuracy
Complexity-based quality indicators for human and social capital in science and research: the case of Serbian Homeland versus Diaspora
No full textWe developed quality indicators model for measuring human and social capital in the scientific and research communities, grounded in the complexity science. The model was implemented in two phases: in the first, we gathered initial data through the questionnaire designed for scientists and researchers; in the second, we fully analyzed all the respondents, according to the model-this included analysis of their CVs, with wider research of their data in all publicly available sources. The research sample included 444 PhD holders, 202 in Homeland and 242 in Diaspora, all of them being of Serbian origin. Among the most significant findings are the facts that Serbian PhDs from its Diaspora, compared with those living in the Homeland, published 4 times more papers, 6 times more in journals with IF; were cited 15 times more, in 14 times more documents; had 13 times higher value of overall IF; had both 5 times higher ResearchGate scores and the h-index values. In achieving all these, they perceived their work in science and research in more entrepreneurial manner and used collaboration strategies: on average, they had 4 times more co-authors than PhDs in the Homeland. On the other hand, PhDs working and living in the Homeland (Serbia) demonstrated higher devotion to the interests of wider communities they belonged to, considered succession planning as more important, and generally felt more afraid of risks that current trends of our civilization, especially regarding the lack of sustainable management, may lead our entire humanity to some form of collapse
A ski injury risk assessment model for ski resorts
No full textWe propose a ski injury risk assessment model which allows ski resorts to take targeted and preventive actions towards critical ski regions. Currently, ski resorts mostly measure ski injury risk based on the ratios constituted of the number of injuries and number of skier days. We argue that this measure can be improved by using ski lift transportation, a more fine-grained measure of risk than skier days. As compared to skier days, which provide a birds-eye view on the risk level of a ski resort, ski lift transportation allows for a spatial-temporal granularity of risk calculation. In this paper, we calculate risk as a measure of injury rate, severity of injuries, and exposure. The model is validated on the data from Kopaonik ski resort, Serbia, which was gathered during five consecutive seasons on more than 17 million ski lift transportation records of nearly 1.45 million skier-days with 1889 reported injuries. During the observed period, the capacity of ski lift transportation system in Kopaonik increased by 58%, and injury rate increased nearly two times, which is due to the emergence of new transportation patterns, as we show in the paper. These patterns heavily influence distribution of injury rates across the ski resort. The proposed model allows for more targeted strategies for injury risk management
Performance comparison of nonlinear and linear regression algorithms coupled with different attribute selection methods for quantitative structure - retention relationships modelling in micellar liquid chromatography
No full textIn micellar liquid chromatography (MLC), the addition of a surfactant to the mobile phase in excess is accompanied by an alteration of its solubilising capacity and a change in the stationary phase's properties. As an implication, the prediction of the analytes' retention in MLC mode becomes a challenging task. Mixed Quantitative Structure - Retention Relationships (QSRR) modelling represents a powerful tool for estimating the analytes' retention. This study compares 48 successfully developed mixed QSRR models with respect to their ability to predict retention of aripiprazole and its five impurities from molecular structures and factors that describe the Brij - acetonitrile system. The development of the models was based on an automatic combining of six attribute (feature) selection methods with eight predictive algorithms and the optimization of hyper-parameters. The feature selection methods included Principal Component Analysis (PCA), Non-negative Matrix Factorization (NMF), ReliefF, Multiple Linear Regression (MLR), Mutual Info and F-Regression. The series of investigated predictive algorithms comprised Linear Regressions (LR), Ridge Regression, Lasso Regression, Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest (RF), Gradient Boosted Trees (GBT) and K-Nearest neighbourhood (k-NN). A sufficient amount of data for building the model (78 cases in total) was provided by conducting 13 experiments for each of the 6 analytes and collecting the target responses afterwards. Different experimental settings were established by varying the values of the concentration of Brij L23, pH of the aqueous phase and acetonitrile content in the mobile phase according to the Box-Behnken design. In addition to the chromatographic parameters, the pool of independent variables was expanded by 27 molecular descriptors from all major groups (physicochemical, quantum chemical, topological and spatial structural descriptors). The best model was chosen by taking into consideration the Root Mean Square Error (RMSE) and cross-validation (CV) correlation coefficient (Q(2)) values. Interestingly, the comparative analysis indicated that a change in the set of input variables had a minor impact on the performance of the final models. On the other hand, different regression algorithms showed great diversity in the ability to learn patterns conserved in the data. In this regard, testing many regression algorithms is necessary in order to find the most suitable technique for model building. In the specific case, GBT-based models have demonstrated the best ability to predict the retention factor in the MLC mode. Steric factors and dipole-dipole interactions have proven to be relevant to the observed retention behaviour. This study, although being of a smaller scale, is a most promising starting point for comprehensive MLC retention prediction
Project Management and Sustainability: Playing Trick or Treat with the Planet
No full textThe incorporation of the social, environmental, and economic dimensions of sustainability in different aspects of human life and business provides a guarantee for our future. Organizations have shown a great interest in incorporating sustainability into managerial concepts, both at the strategic and operational levels. Sustainable business strategies are being implemented in many projects, which has led to a recent expansion of interest in exploring the potential of integrating sustainability dimensions in project management. With the intention of contributing to a better understanding of sustainable project management, this paper examines whether project management methodologies, applied in different sectors, support the introduction of sustainability dimensions. It also surveys the level of integration of sustainability dimensions in groups of project management processes. Considering that the incorporation of sustainability in project management poses numerous challenges for project managers, this paper examines the necessary knowledge and skills required for sustainable project management in different sectors. As part of this research, an empirical survey was conducted in project-oriented organizations from both the public and private sectors. The findings reveal that the application of project management methodologies promotes the introduction of sustainability dimensions, particularly the social aspect, irrespective of the sector, since the processes in projects managed by a specific methodology are consistent with the social elements of sustainability. In the public sector, there is a noticeable lack of knowledge of the meaning and dimensions of sustainability and, accordingly, an urgent need for project managers to gain knowledge and skills pertaining to sustainable project management
An Acceptance Approach for Novel Technologies in Car Insurance
No full textBackground: Unlike other financial services, technology-driven changes in the insurance industry have not been a vastly explored topic in scholarly literature. Incumbent insurance companies have hitherto been holding their positions using the complexity of the product, heavy regulation, and gigantic balance sheets as paramount factors for a relatively slow digitalization and technological transformation. However, new technologies such as car telematic devices have been creating a new insurance ecosystem. The aim of this study is to assess the telematics technology acceptance for insurance purposes. Methods: The study is based on the Unified Theory of Acceptance and Use of Technology (UTAUT). By interviewing 502 new car buyers, we tested the factors that affect the potential usage of telematic devices for insurance purposes. Results: The results indicate that facilitating conditions are the main predictor of telematics use. Moreover, privacy concerns related to the potential abuse of driving behavior data play an important role in technology acceptance. Conclusions: Although novel insurance technologies are mainly presented as user-driven, users (drivers and insurance buyers) are often neglected as an active party in the development of such technologies
A systematic review of China's belt and road initiative: implications for global supply chain management
No full textChina's Belt and Road Initiative (BRI) is one of the world's largest infrastructure projects, with its potential political and economic impact being widely discussed since its inception in 2013. Yet the phenomenon has received only limited attention in the Supply Chain Management (SCM) literature. In response, we first conduct a broad systematic review of the literature to assess how China's BRI is portrayed. Using this as a backdrop, we then distil the likely impact of the BRI on location decisions and supply chain flows. Finally, in a broader discussion of the SCM literature, we explore the implications of the BRI for future research in four key areas: supply chain configuration, supply chain resilience, sustainable SCM, and cross border SCM. While these areas are not new, the BRI presents a unique context that can be used to enhance theory and understanding in each area. The BRI reduces time distance independent of geographical distance by diverting supply chain flows from established routes to new routes via far less accessible regions. This introduces new risks and sustainability issues that call for multi-criteria decision support systems. Another important issue is the adoption and diffusion of the BRI since this will ultimately determine project success
Analytics of Learning Strategies: Role of Course Design and Delivery Modality
No full textGeneralizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning analytics method proposed for detecting learning tactics and strategies from trace data. The method was applied to the datasets collected in three different course designs and delivery modalities, including flipped classroom, blended learning, and massive open online course. The proposed method combines process mining and sequence analysis. The detected learning strategies are explored in terms of their association with academic performance. The results indicate the applicability of the proposed method across different learning contexts. Moreover, the findings contribute to the understanding of the learning tactics and strategies identified in the trace data: learning tactics proved to be responsive to the course design, whereas learning strategies were found to be more sensitive to the delivery modalities than to the course design. These findings, well aligned with self-regulated learning theory, highlight the association of learning contexts with the choice of learning tactics and strategies