Search results for: probabilistic decision tree

Authors: Ali Muhammad

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The study examines the consequences of decision making in Kuwait work organization. The framework used in this study proposes that participation in decision making improves organizational ethical climate, which in turn increases employee’s trust in supervisor and trust in the organization. Furthermore, the model suggests that allowing employees to voice their opinions positively effects their perceptions of organizational justice. Providing employees with the opportunity to participate in decision making (voice), enhances their perceptions of the fairness of those decisions. Allowing employees to express their opinions and feeling about decisions being made show that the organization respect appreciates their views. This feeling of respect and appreciation reflects positively on employee’s perception of justice. Survey data were collected from a sample of 292 employees working in Kuwaiti work organizations. Pearson correlation, non-parametric tests, and structural equation models were used to analyze the data. Results of the analysis show that participation in decision making enhances employee perception of ethical climate, which in turn increases perception organizational justice and organizational trust. Implications of the findings and directions for future research are discussed.

Keywords: participation in decision making, organizational trust, trust in supervisor, organizational justice, ethical climate

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Authors: Mikel Alonso López

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This paper explores, in depth, the idea that emotions are present in all consumer decision making processes, meaning that purchase decisions have never been purely cognitive or as they traditionally have been defined, rational. Human beings, in all kinds of decisions, has "always" used neural systems related to emotions along with neural systems related to cognition, regardless of the type of purchase or the product or service in question. Therefore, all purchase decisions are, at the same time, cognitive and emotional. This paper presents an analysis of the main contributions of researchers in this regard.

Keywords: emotions, decision making, consumer behaviour, emotional behaviour

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Authors: K. Asanimoghadam, M. Salahi, A. Jamalian

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Data envelopment analysis is an approach to measure the efficiency of decision making units with multiple inputs and outputs. The structure of many decision making units also has decision-making subunits that are not considered in most data envelopment analysis models. Also, the inputs and outputs of the decision-making units usually are considered desirable, while in some real-world problems, the nature of some inputs or outputs are undesirable. In this thesis, we study the evaluation of the efficiency of two stage decision-making units, where some outputs are undesirable using two non-radial models, the SBM and the ASBM models. We formulate the nonlinear ASBM model as a second order cone optimization problem. Finally, we compare two models for both external and internal evaluation approaches for two real world example in the presence of undesirable outputs. The results show that, in both external and internal evaluations, the overall efficiency of ASBM model is greater than or equal to the overall efficiency value of the SBM model, and in internal evaluation, the ASBM model is more flexible than the SBM model.

Keywords: network DEA, conic optimization, undesirable output, SBM

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Authors: Arefeh Arabaninezhad, Ali Fakher

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Since the deterministic analysis methods fail to take system uncertainties into account, probabilistic and non-probabilistic methods are suggested. Geotechnical analyses are used to determine the stress and deformation caused by construction; accordingly, many input variables which depend on ground behavior are required for geotechnical analyses. The Random Set approach is an applicable reliability analysis method when comprehensive sources of information are not available. Using Random Set method, with relatively small number of simulations compared to fully probabilistic methods, smooth extremes on system responses are obtained. Therefore random set approach has been proposed for reliability analysis in geotechnical problems. In the present study, the application of random set method in reliability analysis of deep excavations is investigated through three deep excavation projects which were monitored during the excavating process. A finite element code is utilized for numerical modeling. Two expected ranges, from different sources of information, are established for each input variable, and a specific probability assignment is defined for each range. To determine the most influential input variables and subsequently reducing the number of required finite element calculations, sensitivity analysis is carried out. Input data for finite element model are obtained by combining the upper and lower bounds of the input variables. The relevant probability share of each finite element calculation is determined considering the probability assigned to input variables present in these combinations. Horizontal displacement of the top point of excavation is considered as the main response of the system. The result of reliability analysis for each intended deep excavation is presented by constructing the Belief and Plausibility distribution function (i.e. lower and upper bounds) of system response obtained from deterministic finite element calculations. To evaluate the quality of input variables as well as applied reliability analysis method, the range of displacements extracted from models has been compared to the in situ measurements and good agreement is observed. The comparison also showed that Random Set Finite Element Method applies to estimate the horizontal displacement of the top point of deep excavation. Finally, the probability of failure or unsatisfactory performance of the system is evaluated by comparing the threshold displacement with reliability analysis results.

Keywords: deep excavation, random set finite element method, reliability analysis, uncertainty

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Authors: S. Anastasiou, C. Nathanailides

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There is considerable evidence to suggest that employees participation in the decision-making process of an organisation, has a positive effect on job satisfaction and work performance of the employees. The purpose of the present work was to examine the HRM practices, demographics and the level of job satisfaction of employees in Greek Aquaculture fish farms. A survey of employees (n=86) in 6 Greek Aquaculture Firms was carried out. The results indicate that HRM practices such as recruitment of the personnel and communication between the departments did not vary between different firms. The most frequent method of recruitment was through the professional network or the personal network of the managers. The preferred method of HRM communication was through the line managers and through group meeting. The level of job satisfaction increased with work experience participation and participation in the decision making process. A high percentage of the employees (81,3%±8.39) felt that they frequently participated in the decision making process. The Aquaculture employees exhibited high level of job satisfaction (88,1±6.95). The level of job satisfaction was related with participation in the decision making process (-0.633, P<0.05) but was not related with as age or gender. In terms of the working conditions, employees were mostly satisfied with their work itself, their colleagues and mostly dissatisfied with working hours, salary issues and low prospects of pay rises.

Keywords: aquaculture, human resources, job satisfaction

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Authors: Shidrokh Goudarzi, Wan Haslina Hassan

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Heterogeneous wireless networks are converging towards an all-IP network as part of the so-called next-generation network. In this paradigm, different access technologies need to be interconnected; thus, vertical handovers or vertical handoffs are necessary for seamless mobility. In this paper, we conduct a review of existing vertical handover decision-making mechanisms that aim to provide ubiquitous connectivity to mobile users. To offer a systematic comparison, we categorize these vertical handover measurement and decision structures based on their respective methodology and parameters. Subsequently, we analyze several vertical handover approaches in the literature and compare them according to their advantages and weaknesses. The paper compares the algorithms based on the network selection methods, complexity of the technologies used and efficiency in order to introduce our vertical handover decision framework. We find that vertical handovers on heterogeneous wireless networks suffer from the lack of a standard and efficient method to satisfy both user and network quality of service requirements at different levels including architectural, decision-making and protocols. Also, the consolidation of network terminal, cross-layer information, multi packet casting and intelligent network selection algorithm appears to be an optimum solution for achieving seamless service continuity in order to facilitate seamless connectivity.

Keywords: heterogeneous wireless networks, vertical handovers, vertical handover metric, decision-making algorithms

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Authors: Seyyedeh Mahdis Mousavi, Masoud Maghsoudi, Zahra Vahed

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The purpose of this paper is to examine the relationship between emotional intelligence as conceptualized in Goleman’s competency model, and decision making styles in levels of management. To conduct this study, different level managers in Iran Broadcasting Organization completed a questionnaire on emotional intelligence and decision making styles. Researcher used descriptive and inferential statistics to describe data and analyze the two variables relationship in managers of three levels. Results revealed significant relationships for rational, dependent, avoidant, and spontaneous styles. No significant relationship was found for intuitive style. Yet the results indicate that avoidant style has negative relation to EI. Furthermore, EI has direct and strong relation to rational style.

Keywords: emotional intelligence (EI), decision making styles, Islamic Republic of Iran Broadcasting (IRIB), Iranian manager

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Authors: Salma Akter, Mohammad M. Haque, Lawrence Akwetey

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An empirical research design will analyze different factors/predictors children use to influence their parents in the family buying decision process in the unexplored area of British Bangladeshi children in the United Kingdom. The proposed conceptual model of factors- buying decision making process will be tested by the Structure Equation Model. A structured Questionnaire and secondary sources will employ to collect data and analyse and measure the validity by Statistical tools (SPSS) and Microsoft Excel. The Contemporary research aims to use the deductive approach developing the research questions and testing the hypothesis to identify the impact of different strategies British Bangladeshi children used to influence their parents in the family buying decision which was overlooked in the previous research.

Keywords: British Bangladeshi children, buying decision process, children influence, influential factors

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Authors: Bincy Mathew, B. William Dharma Raja

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Successful decision making in a social setting depends on the ability to understand the intentions, emotions and beliefs of others. Children live and grow in the social world. Individuals think to satisfy their curiosity and mush of their social thought is practical, to attain their goal. Children’s thought about their social world influences how they behave towards it. The main purpose of this paper is to review the influence of decision making on adjustment behaviour of visually challenged adolescents. The sample was purposively selected to study the cases of two of the visually challenged adolescents from a Special School, in Tirunelveli, Tamil Nadu, India. The authors appraised the observed behaviour of adjustment in these children. It may be concluded that the social cognitive ability of decision making is at least, to certain extent, influences adjustment behaviour of visually challenged adolescents. Adjustment behaviour attempts to maintain a child’s level of physiological and psychological equilibrium and it is directed towards tension reduction. It involves a state of harmonious relationship existing between the individual and one’s environment so that adjustment is a matter of interaction between the capacities of the individual and the demands of the environment. The study also found that music induces a receptive mood that generally enhances cognitive processing and every decision that the child makes has its brunt on the behaviour. It is solely based on the case study carried out by the authors.

Keywords: social cognition, decision making, adjustment behaviour, adolescents

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Authors: Boris Djartov, Sanaz Mostaghim

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This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

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Authors: Ali Jahanfar, Brajesh Dubey, Bahram Gharabaghi, Saber Bayat Movahed

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Ever increasing population growth of major urban centers and environmental challenges in siting new landfills have resulted in a growing trend in design of mega-landfills some with extraordinary heights and dangerously steep slopes. Landfill failure mobility risk analysis is one of the most uncertain types of dynamic rheology models due to very large inherent variabilities in the heterogeneous solid waste material shear strength properties. The waste flow of three historic dumpsite and two landfill failures were back-analyzed using run-out modeling with DAN-W model. The travel distances of the waste flow during landfill failures were calculated approach by taking into account variability in material shear strength properties. The probability distribution function for shear strength properties of the waste material were grouped into four major classed based on waste material compaction (landfills versus dumpsites) and composition (high versus low quantity) of high shear strength waste materials such as wood, metal, plastic, paper and cardboard in the waste. This paper presents a probabilistic method for estimation of the spatial extent of waste avalanches, after a potential landfill failure, to create maps of vulnerability scores to inform property owners and residents of the level of the risk.

Keywords: landfill failure, waste flow, Voellmy rheology, friction coefficient, waste compaction and type

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Authors: Inayah Hidayati

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Innovation in communication technology has opened up opportunities for student to migrate and study abroad. The increasing number of Indonesian students migrating to study abroad suggests the importance of understanding the reason underline their movements. Objective: This research aims to explain the migration decision-making process of Indonesian student migrants in Europe. In detail, this research will consider the innovation in communication technology in the migration decision-making process of students who emigrated from Indonesia and how they use that in the context of the migration decision-making process. Methods: The data collected included qualitative data from in-depth interviews. An interview guide was formulated to facilitate the in-depth interviews and generate a better understanding of migration behavior. Expectation: 1). Innovation in communication technology help Indonesian student migrants on migration decision making process. 2). Student migrants use communication technology platforms for searching information about destination area. Result: Student migrant in Europe use their communication technology platforms to gain information before they choose that country for study. They use WhatsApp and LINE to making contact with their friends and colleagues in the destination country. WhatsApp and LINE group help Indonesian student to get information about school and daily life.

Keywords: international migration, student, decision making process, communication technology platforms

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Authors: Sai Sudarshan, Harsh Vyas, Riddhiman Sherlekar

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The oil and gas industry has been unwilling to adopt stochastic definition of reserves. Nevertheless, Monte Carlo simulation methods have gained acceptance by engineers, geoscientists and other professionals who want to evaluate prospects or otherwise analyze problems that involve uncertainty. One of the common applications of Monte Carlo simulation is the estimation of recoverable hydrocarbon from a reservoir.Monte Carlo Simulation makes use of random samples of parameters or inputs to explore the behavior of a complex system or process. It finds application whenever one needs to make an estimate, forecast or decision where there is significant uncertainty. First, the project focuses on performing Monte-Carlo Simulation on a given data set using U. S Department of Energy’s MonteCarlo Software, which is a freeware e&p tool. Further, an algorithm for simulation has been developed for MATLAB and program performs simulation by prompting user for input distributions and parameters associated with each distribution (i.e. mean, st.dev, min., max., most likely, etc.). It also prompts user for desired probability for which reserves are to be calculated. The algorithm so developed and tested in MATLAB further finds implementation in Python where existing libraries on statistics and graph plotting have been imported to generate better outcome. With PyQt designer, codes for a simple graphical user interface have also been written. The graph so plotted is then validated with already available results from U.S DOE MonteCarlo Software.

Keywords: simulation, probability, confidence interval, sensitivity analysis

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Authors: Y. de Smet, J. Hubinont

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PROMETHEE and GAIA are well-known Multiple Criteria Decision Aid methods. Given an evaluation table and preference parameters they allow to rank the alternatives, to visualize the problem, to perform sensitivity and robustness analysis, etc. Unfortunately, it is often hard for the Decision Maker (DM) to estimate the precise values of these parameters. Therefore an alternative option is to give ranges of potential values in order to apply Stochastic Multicriteria Acceptability Analysis. This has been recently studied in the context of the SMAA-PROMETHEE method. The aim of this contribution is to propose an SMAA extension of GAIA. We show how this tool can be useful and provide complementary information to SMAA-PROMETHEE. This is illustrated on a pedagogical example.

Keywords: multiple criteria decision making, PROMETHEE, GAIA, SMAA

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Authors: Cate MacMillan, Nicholas J. Stevens, Johanna Rosier, Steven Boyd

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Choosing where to live is an important decision for anybody, however, this decision is more complex if you are an adult with intellectual disability. Our research asked adults with intellectual disability, parents and carers and disability, housing and built environment decision makers what they considered important in deciding where to live. If medical advances continue to improve the longevity of adults with intellectual disability, many of these adults will outlive their parents. With appropriate community support, and in appropriately designed neighbourhoods, many will be able to live independently. Our research suggests that the key to achieving independent living as an adult with intellectual disability is not so much about the house but the type of neighbourhood and its design. This paper presents the results of interviews and details a practical approach which will better inform urban development decision-makers in establishing safe, inclusive and accessible neighbourhood design.

Keywords: inclusion, independent living, intellectual disability, neighbourhoods, systems thinking, urban design and planning

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Authors: Nattapong Techarattanased, Paweena Sribunrueng

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The objective of this study is to investigate strategies in customer relationship management and customers’ behavior in making decision on buying car insurance of Southeast Insurance Co. Ltd. in Bangkok. Subjects in this study included 400 customers with the age over 20 years old to complete questionnaires. The data were analyzed by arithmetic mean and multiple regressions. The results revealed that the customers’ opinions on the strategies in customer relationship management, i.e. customer relationship, customer feedback, customer follow-up, useful service suggestions, customer communication, and service channels were in moderate level but on the customer retention was in high level. Moreover, the strategy in customer relationship management, i.e. customer relationship, and customer feedback had an influence on customers’ buying decision on buying car insurance. The two factors above can be used for the prediction at the rate of 34%. In addition, the strategy in customer relationship management, i.e. customer retention, customer feedback, and useful service suggestions had an influence on the customers’ buying decision on period of being customers. The three factors could be used for the prediction at the rate of 45%.

Keywords: strategies, customer relationship management, behavior in buying decision, car insurance

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Authors: Saurav Kumar Suman, P. Karthigayani

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In this paper the height of the tree is estimated and forest types is classified from the multi temporal RISAT-1 Horizontal-Horizontal (HH) and Horizontal-Vertical (HV) Polarised Satellite Aperture Radar (SAR) data. The novelty of the proposed project is combined use of the Back-scattering Coefficients (Sigma Naught) and the Coherence. It uses Water Cloud Model (WCM). The approaches use two main steps. (a) Extraction of the different forest parameter data from the Product.xml, BAND-META file and from Grid-xxx.txt file come with the HH & HV polarized data from the ISRO (Indian Space Research Centre). These file contains the required parameter during height estimation. (b) Calculation of the Vegetation and Ground Backscattering, Coherence and other Forest Parameters. (c) Classification of Forest Types using the ENVI 5.0 Tool and ROI (Region of Interest) calculation.

Keywords: RISAT-1, classification, forest, SAR data

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Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

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The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: data mining, knowledge discovery in databases, prediction models, student success

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Authors: Mária Hudáková, Vladimír Míka, Katarína Hollá

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Making decisions is the core of management and a result of conscious activities which is under way in a particular environment and concrete conditions. The managers decide about the goals, procedures and about the methods how to respond to the changes and to the problems which developed. Their decisions affect the effectiveness, quality, economy and the overall successfulness in every organisation. In spite of this fact, they do not pay sufficient attention to the individual steps of the decision-making process. They emphasise more how to cope with the individual methods and techniques of making decisions and forget about the way how to cope with analysing the problem or assessing the individual solution variants. In many cases, the underestimating of the analytical phase can lead to an incorrect assessment of the problem and this can then negatively influence its further solution. Based on our analysis of the theoretical solutions by individual authors who are dealing with this area and the realised research in Slovakia and also abroad we can recognise an insufficient interest of the managers to assess the risks in the decision-making process. The goal of this paper is to assess the risks in the managers´ decision-making process relating to the conditions of the environment, to the subject’s activity (the manager’s personality), to the insufficient assessment of individual variants for solving the problems but also to situations when the arisen problem is not solved. The benefit of this paper is the effort to increase the need of the managers to deal with the risks during the decision-making process. It is important for every manager to assess the risks in his/her decision-making process and to make efforts to take such decisions which reflect the basic conditions, states and development of the environment in the best way and especially for the managers´ decisions to contribute to achieving the determined goals of the organisation as effectively as possible.

Keywords: risk, decision-making, manager, process, analysis, source of risk

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Authors: Masood Karamoozian, Zhang Hong

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The necessity and complexity of the decision-making process and the interference of the various factors to make decisions and consider all the relevant factors in a problem are very obvious nowadays. Hence, researchers show their interest in multi-criteria decision-making methods. In this research, the Analytical Hierarchy Process (AHP), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods of multi-criteria decision-making have been used to solve the problem of optimal construction systems. Systems being evaluated in this problem include; Light Steel Frames (LSF), a case study of designs by Zhang Hong studio in the Southeast University of Nanjing, Insulating Concrete Form (ICF), Ordinary Construction System (OCS), and Prefabricated Concrete System (PRCS) as another case study designs in Zhang Hong studio in the Southeast University of Nanjing. Crowdsourcing was done by using a questionnaire at the sample level (200 people). Questionnaires were distributed among experts, university centers, and conferences. According to the results of the research, the use of different methods of decision-making led to relatively the same results. In this way, with the use of all three multi-criteria decision-making methods mentioned above, the Prefabricated Concrete System (PRCS) was in the first rank, and the Light Steel Frame (LSF) system ranked second. Also, the Prefabricated Concrete System (PRCS), in terms of performance standards and economics, was ranked first, and the Light Steel Frame (LSF) system was allocated the first rank in terms of environmental standards.

Keywords: multi-criteria decision making, AHP, SAW, TOPSIS

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Authors: Humayun Murshed, Shibly Abdullah

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The research conducted in early seventies apparently assumed the existence of a universal decision model for union negotiators and furthermore tended to regard financial information as a ‘neutral’ input into a rational decision-making process. However, research in the eighties began to question the neutrality of financial information as an input in collective bargaining rather viewing it as a potentially effective means for controlling the labour force. Furthermore, this later research also started challenging the simplistic assumptions relating particularly to union objectives which have underpinned the earlier search for universal union decision models. Despite the above developments there seems to be a dearth of studies in developing countries concerning the use of financial information in collective bargaining. This paper seeks to begin to remedy this deficiency. Utilising a case study approach based on two enterprises, one in the public sector and the other a multinational, the universal decision model is rejected and it is argued that the decision whether or not to use financial information is a contingent one and such a contingency is largely defined by the context and environment in which both union and management negotiators work. An attempt is also made to identify the factors constraining as well as promoting the use of financial information in collective bargaining, these being regarded as unique to the organizations within which the case studies are conducted.

Keywords: collective bargaining, developing countries, disclosures, financial information

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Authors: Humphrey Agevi, Harrison Tsingalia, Richard Onwonga, Shem Kuyah

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Most of the world ecosystems have been affected by the effects of climate change. Efforts have been made to mitigate against climate change effects. While most studies have been done in forest ecosystems and pure plant plantations, trees on farms including agroforestry have only received attention recently. Agroforestry systems and tree cover on agricultural lands make an important contribution to climate change mitigation but are not systematically accounted for in the global carbon budgets. This study sought to: (i) determine tree diversity in different agroforestry practices; (ii) determine tree biomass in different agroforestry practices. Study area was determined according to the Land degradation surveillance framework (LSDF). Two study sites were established. At each of the site, a 5km x 10km block was established on a map using Google maps and satellite images. Way points were then uploaded in a GPS helped locate the blocks on the ground. In each of the blocks, Nine (8) sentinel clusters measuring 1km x 1km were randomized. Randomization was done in a common spreadsheet program and later be downloaded to a Global Positioning System (GPS) so that during surveys the researchers were able to navigate to the sampling points. In each of the sentinel cluster, two farm boundaries were randomly identified for convenience and to avoid bias. This led to 16 farms in Kakamega South and 16 farms in Kakamega North totalling to 32 farms in Kakamega Site. Species diversity was determined using Shannon wiener index. Tree biomass was determined using allometric equation. Two agroforestry practices were found; homegarden and hedgerow. Species diversity ranged from 0.25-2.7 with a mean of 1.8 ± 0.10. Species diversity in homegarden ranged from 1-2.7 with a mean of 1.98± 0.14. Hedgerow species diversity ranged from 0.25-2.52 with a mean of 1.74± 0.11. Total Aboveground Biomass (AGB) determined was 13.96±0.37 Mgha-1. Homegarden with the highest abundance of trees had higher above ground biomass (AGB) compared to hedgerow agroforestry. This study is timely as carbon budgets in the agroforestry can be incorporated in the global carbon budgets and improve the accuracy of national reporting of greenhouse gases.

Keywords: agroforestry, allometric equations, biomass, climate change

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Authors: Erfan Izadpanah

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The present study was conducted to investigate the effect of the Trans-Cranial Direct Current Stimulation (tDCS) on cognitive flexibility and social decision-making in skilled, semi-skilled and novice football players. The present quasi-experimental pretest-posttest study was conducted on 60 randomly-selected subjects divided into trial and placebo groups (n=30 per group). The trial group received three 20-minute sessions of anodic stimulation at the intensity of 2 mA. The placebo group also received three sessions of sham anodic stimulation. Data were collected using the Wisconsin, Grant and Berg Card-Sorting Test (1948) and the ultimatum game and were then analyzed using the ANCOVA. The results showed significant differences between the skilled, semi-skilled and novice football players in the trial and placebo groups in terms of cognitive flexibility and social decision-making (P<0.01). TDCS appears to be able to improve cognitive flexibility and consequently social decision-making in football players and is recommended to sport psychologists and coaches as a useful intervention to increase cognitive flexibility and improve social decision-making in players.

Keywords: TDCS, cognitive flexibility, social decision-making, skilled, semi-skilled and novice football players

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Authors: Hatice Esra Akgül, Celaleddin Öztürk

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Lichen biodiversity in forests is controlled by environmental conditions. Epiphytic lichens have some degree of substrate specificity. Diversity and distribution of epiphytic lichens are affected by humidity, light, altitude, temperature, bark pH of the trees.This study describes the epiphytic lichen communities with comparing their preferred tree species. 34 epiphytic lichen taxa are reported on Pinus sp. L., Quercus sp. L., Fagus sp. L., Carpinus sp. L., Abies sp. Mill., Fraxinus sp. Tourn. ex L. from different altitudes around the Şeker Canyon (Karabük, Turkey). 11 of these taxa are growing on Quercus sp., 10 of them are growing on Fagus sp., 7 of them are growing on Pinus sp., 4 of them are on Carpinus sp., 2 of them are on Abies sp. and one of them is on Fraxinus sp. Evernia prunastri (L.) Ach. is growing on both of Fagus sp. and Quercus sp. Lecanora pulicaris (Pers.) Ach. is growing on both of Abies sp. and Quercus sp.

Keywords: biodiversity, epiphytic lichen, forest, Turkey

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Authors: Mogale Sabone, Thabiso Ntlole

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The pressure from globalization has made manufacturing organizations to move towards three major competitive arenas: quality, cost, and responsiveness. Quality is a universal value and has become a global issue. In order to survive and be able to provide customers with good products, manufacturing organizations’ supporting systems, tools, and structures it uses must grow or evolve. The majority of quality management concepts and strategies that are practiced recently are aimed at detecting and correcting problems which already exist and serve to limit losses. In agile manufacturing environment there is no room for defect and error so it needs a quality management which is proactively directed at problem prevention. This proactive quality management avoids losses by focusing on failure prevention, virtual elimination of the possibility of premature failure, mistake-proofing, and assuring consistently high quality in the definition and design of creation processes. To achieve this, a decision support tool for quality control and management is suggested. Current decision support tools/methods used by most manufacturing companies in Botswana for quality management and control are not integrated, for example they are not consistent since some tests results data is recorded manually only whilst others are recorded electronically. It is only a set of procedures not a tool. These procedures cannot offer interactive decision support. This point brings to light the aim of this research which is to develop a framework which will help manufacturing companies in Botswana build a decision support tool for quality control and management.

Keywords: decision support tool, manufacturing, quality control, quality management

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Stefan K. Behfar

Abstract:

The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Ayham Fattoum, Simos Chari, Duncan Shaw

Abstract:

Volatile, uncertain, complex, and ambiguous (VUCA) conditions threaten systems viability with emerging and novel events requiring immediate and localized responses. Such responsiveness is only possible through devolved freedom and emancipated decision-making. The Viable System Model (VSM) recognizes the need and suggests maximizing autonomy to localize decision-making and minimize residual complexity. However, exercising delegated autonomy in VUCA requires confidence and knowledge to use intuition and guidance to maintain systemic coherence. This paper explores the role of intuition as an enabler of emancipated decision-making and autonomy under VUCA. Intuition allows decision-makers to use their knowledge and experience to respond rapidly to novel events. This paper offers three contributions to VSM. First, it designs a system model that illustrates the role of intuitive decision-making in managing complexity and maintaining viability. Second, it takes a black-box approach to theory development in VSM to model the role of autonomy and intuition. Third, the study uses a multi-stage discovery-oriented approach (DOA) to develop theory, with each stage combining literature, data analysis, and model/theory development and identifying further questions for the subsequent stage. We synthesize literature (e.g., VSM, complexity management) with seven months of field-based insights (interviews, workshops, and observation of a live disaster exercise) to develop a framework of intuitive complexity management framework and VSM models. The results have practical implications for enhancing the resilience of organizations and communities.

Keywords: Intuition, complexity management, decision-making, viable system model

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Authors: Haikal Achmad Thaha, Pujo Laksono, Dhamma Nibbana Putra

Abstract:

Customer service is one of the core interest in a service sector of a company, whether as the core business or as service part of the operation. Most of the time, the people and the previous research in service industry is focused on finding the best business model solution for the service sector, usually to decide between total in house customer service, outsourcing, or something in between. Conventionally, to take this decision is some important part of the management job, and this is a process that usually takes some time and staff effort, meanwhile market condition and overall company needs may change and cause loss of income and temporary disturbance in the companies operation . However, in this paper we have offer a new concept model to assist decision making process in service industry. This model will featured information platform as central tool to integrate service industry operation. The result is service information model which would ideally increase response time and effectivity of the decision making. it will also help service industry in switching the service solution system quickly through machine learning when the companies growth and the service solution needed are changing.

Keywords: service industry, customer service, machine learning, decision making, information platform

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Authors: Ashish Kumar, Kaptan Singh, Amit Saxena

Abstract:

Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.

Keywords: K-nearest neighbor, random forest, decision tree, pre-processing

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