Search results for: decision tree model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 20214

Search results for: decision tree model

19524 Decision Making to Study Abroad among Indonesian Student Migrants in Europe: The Role of Communication Technology

Authors: Inayah Hidayati

Abstract:

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

Procedia PDF Downloads 243
19523 Smaa-Gaia: A Complementary Tool of the Smaa-Promethee Method

Authors: Y. de Smet, J. Hubinont

Abstract:

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

Procedia PDF Downloads 429
19522 Neighbourhood Design for Independent Living of Adults with Intellectual Disability

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

Abstract:

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

Procedia PDF Downloads 358
19521 Strategies in Customer Relationship Management and Customers’ Behavior in Making Decision on Buying Car Insurance of Southeast Insurance Co. Ltd. in Bangkok

Authors: Nattapong Techarattanased, Paweena Sribunrueng

Abstract:

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

Procedia PDF Downloads 406
19520 AER Model: An Integrated Artificial Society Modeling Method for Cloud Manufacturing Service Economic System

Authors: Deyu Zhou, Xiao Xue, Lizhen Cui

Abstract:

With the increasing collaboration among various services and the growing complexity of user demands, there are more and more factors affecting the stable development of the cloud manufacturing service economic system (CMSE). This poses new challenges to the evolution analysis of the CMSE. Many researchers have modeled and analyzed the evolution process of CMSE from the perspectives of individual learning and internal factors influencing the system, but without considering other important characteristics of the system's individuals (such as heterogeneity, bounded rationality, etc.) and the impact of external environmental factors. Therefore, this paper proposes an integrated artificial social model for the cloud manufacturing service economic system, which considers both the characteristics of the system's individuals and the internal and external influencing factors of the system. The model consists of three parts: the Agent model, environment model, and rules model (Agent-Environment-Rules, AER): (1) the Agent model considers important features of the individuals, such as heterogeneity and bounded rationality, based on the adaptive behavior mechanisms of perception, action, and decision-making; (2) the environment model describes the activity space of the individuals (real or virtual environment); (3) the rules model, as the driving force of system evolution, describes the mechanism of the entire system's operation and evolution. Finally, this paper verifies the effectiveness of the AER model through computational and experimental results.

Keywords: cloud manufacturing service economic system (CMSE), AER model, artificial social modeling, integrated framework, computing experiment, agent-based modeling, social networks

Procedia PDF Downloads 81
19519 The Voluntary Audit of Semi-Annual Consolidated Financial Statements Decision and Accounting Conservatism

Authors: Shuofen Hsu, Ya-Yi Chao, Chao-Wei Li

Abstract:

This paper investigates the relationship between voluntary audit (hereafter, VA) of semi-annual consolidated financial statements decision and accounting conservatism. In general, there are four kinds of auditors' assurance services, which include audit, review, agreed-upon procedure and compliance engagements base on degree of assurance. The VA work by auditors may not only have the higher audit quality but an important signal of more reliable information than the review work. In Taiwan, The listed companies must prepare the semi-annual consolidated financial statements and with auditors' review before 2012, but some of the listed companies choose the assurance work from review to audit voluntarily. Due to the adoption of International Financial Reporting Standards, the listed companies were required to prepare the second quarterly consolidated financial statements which should be reviewed by auditors since 2013. This rule will change some of the assurance work from audit to review by auditors, and the information asymmetry maybe increased. To control the selection bias, we use two-stage model to test the relationship between VA decision and accounting conservatism. Our empirical results indicate that the VA decision and accounting conservatism have a significant positive relationship in firms with family-controlled. That is, firms with family-controlled are more likely to do VA and to prepare more conservative consolidated financial statements to reduce the information asymmetry, meaning that there is a complementary effect between VA and accounting conservatism for firms with more information asymmetry. But on the contrary, we find that the VA decision and accounting conservatism have a significant negative relationship in firms with professional managers-controlled, meaning that there is a substitution effect between VA and accounting conservatism for firms with less information asymmetry. Finally, the accounting conservatism of consolidated financial statements decrease after the adoption of IFRSs (International Financial Reporting Standards) in Taiwan. It means that the disclosure and transparency of consolidated financial statements had be improved.

Keywords: voluntary audit, accounting conservatism, audit quality, information asymmetry

Procedia PDF Downloads 226
19518 Commitment Based Revenue Sharing Contract

Authors: Muhammad Shafiq, Huynh Trung Luong

Abstract:

In this paper, we proposed a commitment based revenue sharing contract for a supply chain comprising one manufacturer and one retailer facing highly uncertain demand of a short life span fashionable product. In our model, the retailer reserves a commitment level with the manufacturer prior to the selling season. In response, the manufacturer allocates and produces a specific quantity which is the maximum available quantity for the retailer. The retailer is motivated to commit more by offering higher revenue sharing percentage for reserved capacity than non-reserved capacity. Due to asymmetric information, it is found that the manufacturer can optimize quantity allocation decision while the commitment level decision of the retailer may not be optimal.

Keywords: supply chain coordination, revenue sharing contract, commitment based revenue sharing, quantity allocation

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19517 Mosquito Repellent Finishing of Cotton Using Pepper Tree (Schinus molle) Seed Oil Extract

Authors: Granch Berhe Tseghai, Tekalgn Gebremedhin Belay, Abrehaley Hagos Gebremariam

Abstract:

Mosquito repellent textiles are one of the most growing ways to advance the textile field by providing the needed characteristics of protecting against mosquitoes, especially in the tropical areas. These types of textiles ensure the protection of human beings from the mosquitoes and the mosquito-borne disease includes malaria, filariasis and dengue fever. In this work Schinus Molle oil (pepper tree oil) was used for mosquito repellent finish as a preformatted thing. This study focused on the penetration of mosquito repellent finish in textile applications as well as nature based alternatives to commercial chemical mosquito repellents in the market. Suitable techniques and materials to achieve mosquito repellency are discussed and pointed out according to our project. In this study textile, sample was treated with binder and schinus oil. The different property has been studied for effective mosquito repellency.

Keywords: cotton, Schinus molle seed oil, mosquito repellent, mosquito-borne diseases

Procedia PDF Downloads 288
19516 A Decision-Support Tool for Humanitarian Distribution Planners in the Face of Congestion at Security Checkpoints: A Real-World Case Study

Authors: Mohanad Rezeq, Tarik Aouam, Frederik Gailly

Abstract:

In times of armed conflicts, various security checkpoints are placed by authorities to control the flow of merchandise into and within areas of conflict. The flow of humanitarian trucks that is added to the regular flow of commercial trucks, together with the complex security procedures, creates congestion and long waiting times at the security checkpoints. This causes distribution costs to increase and shortages of relief aid to the affected people to occur. Our research proposes a decision-support tool to assist planners and policymakers in building efficient plans for the distribution of relief aid, taking into account congestion at security checkpoints. The proposed tool is built around a multi-item humanitarian distribution planning model based on multi-phase design science methodology that has as its objective to minimize distribution and back ordering costs subject to capacity constraints that reflect congestion effects using nonlinear clearing functions. Using the 2014 Gaza War as a case study, we illustrate the application of the proposed tool, model the underlying relief-aid humanitarian supply chain, estimate clearing functions at different security checkpoints, and conduct computational experiments. The decision support tool generated a shipment plan that was compared to two benchmarks in terms of total distribution cost, average lead time and work in progress (WIP) at security checkpoints, and average inventory and backorders at distribution centers. The first benchmark is the shipment plan generated by the fixed capacity model, and the second is the actual shipment plan implemented by the planners during the armed conflict. According to our findings, modeling and optimizing supply chain flows reduce total distribution costs, average truck wait times at security checkpoints, and average backorders when compared to the executed plan and the fixed-capacity model. Finally, scenario analysis concludes that increasing capacity at security checkpoints can lower total operations costs by reducing the average lead time.

Keywords: humanitarian distribution planning, relief-aid distribution, congestion, clearing functions

Procedia PDF Downloads 82
19515 Design and Implementation of an Effective Machine Learning Approach to Crime Prediction and Prevention

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

Procedia PDF Downloads 94
19514 Predicting the Impact of Scope Changes on Project Cost and Schedule Using Machine Learning Techniques

Authors: Soheila Sadeghi

Abstract:

In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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19513 Evidence Theory Based Emergency Multi-Attribute Group Decision-Making: Application in Facility Location Problem

Authors: Bidzina Matsaberidze

Abstract:

It is known that, in emergency situations, multi-attribute group decision-making (MAGDM) models are characterized by insufficient objective data and a lack of time to respond to the task. Evidence theory is an effective tool for describing such incomplete information in decision-making models when the expert and his knowledge are involved in the estimations of the MAGDM parameters. We consider an emergency decision-making model, where expert assessments on humanitarian aid from distribution centers (HADC) are represented in q-rung ortho-pair fuzzy numbers, and the data structure is described within the data body theory. Based on focal probability construction and experts’ evaluations, an objective function-distribution centers’ selection ranking index is constructed. Our approach for solving the constructed bicriteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a matrix, the columns of which allow us to find all possible partitionings of the HADCs with the service centers. Some constraints are also taken into consideration while generating the matrix. In the second phase, based on the matrix and using our exact algorithm, we find the partitionings -allocations of the HADCs to the centers- which correspond to the Pareto-optimal solutions. For an illustration of the obtained results, a numerical example is given for the facility location-selection problem.

Keywords: emergency MAGDM, q-rung orthopair fuzzy sets, evidence theory, HADC, facility location problem, multi-objective combinatorial optimization problem, Pareto-optimal solutions

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19512 Mycorrhizal Autochthonous Consortium Induced Defense-Related Mechanisms of Olive Trees against Verticillium dahliae

Authors: Hanane Boutaj, Abdelilah Meddich, Said Wahbi, Zainab El Alaoui-Talibi, Allal Douira, Abdelkarim Filali-Maltouf, Cherkaoui El Modafar

Abstract:

The present work aims to investigate the effect of arbuscular mycorrhizal fungi (AMF) in improving the olive tree resistance to Verticillium wilt caused by Verticillium dahliae. Inoculated plants with a mycorrhizal autochthonous consortium 'Rhizolive consortium' and pure strain 'Glomus irregulare' were infected after three months with V. dahliae. The improving of olive tree resistance was determined through disease severity, incidence, and defoliation. On the other hand, the defense mechanisms of olive plants were evaluated through lignin content, phenylalanine ammonia lyase (PAL) activity, and polyphenol content. The results revealed that both AMF significantly (p < 0.05) reduced disease development and the rate of defoliation in infected olive plants. Moreover, the contents of lignin were boosted after mycorrhizal inoculation in both the roots and the stems of olive plants, which remained significantly (p < 0.001) higher after the 90th days of V. dahliae inoculation. PAL activity was increased after V. dahliae inoculation in the stems of 'Rhizolive consortium' treatment that were 17 times higher than those in the roots of olive plants. The polyphenol content in the stems was about twice higher than those in the roots. The reduction of disease severity was accompanied by increased levels of lignin content, PAL activity, and polyphenol content, particularly in the stems of olive plants, indicating the strengthening of the olive plant immune system against V. dahliae.

Keywords: olive tree, Mycorrhizal autochthonous consortium, Glomus irregulare, Verticillium dahliae, defense mechanisms

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19511 Evaluation of Robust Feature Descriptors for Texture Classification

Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

Abstract:

Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets - UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

Procedia PDF Downloads 371
19510 Importance of Risk Assessment in Managers´ Decision-Making Process

Authors: Mária Hudáková, Vladimír Míka, Katarína Hollá

Abstract:

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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19509 Composite Kernels for Public Emotion Recognition from Twitter

Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

Abstract:

The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

Procedia PDF Downloads 219
19508 Optimal Construction Using Multi-Criteria Decision-Making Methods

Authors: Masood Karamoozian, Zhang Hong

Abstract:

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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19507 Hybrid Adaptive Modeling to Enhance Robustness of Real-Time Optimization

Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

Abstract:

Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

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19506 Stochastic Optimization of a Vendor-Managed Inventory Problem in a Two-Echelon Supply Chain

Authors: Bita Payami-Shabestari, Dariush Eslami

Abstract:

The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

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19505 The Effect of Trans-Cranial Direct Current Stimulation (tDCS) on Cognitive Flexibility and Social Decision-Making in Football Players

Authors: Erfan Izadpanah

Abstract:

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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19504 Framework for Decision Support Tool for Quality Control and Management in Botswana Manufacturing Companies

Authors: Mogale Sabone, Thabiso Ntlole

Abstract:

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

Procedia PDF Downloads 566
19503 Unspoken Playground Rules Prompt Adolescents to Avoid Physical Activity: A Focus Group Study of Constructs in the Prototype Willingness Model

Authors: Catherine Wheatley, Emma L. Davies, Helen Dawes

Abstract:

The health benefits of exercise are widely recognised, but numerous interventions have failed to halt a sharp decline in physical activity during early adolescence. Many such projects are underpinned by the Theory of Planned Behaviour, yet this model of rational decision-making leaves variance in behavior unexplained. This study investigated whether the Prototype Willingness Model, which proposes a second, reactive decision-making path to account for spontaneous responses to the social environment, has potential to improve understanding of adolescent exercise behaviour in school by exploring constructs in the model with young people. PE teachers in 4 Oxfordshire schools each nominated 6 pupils who were active in school, and 6 who were inactive, to participate in the study. Of these, 45 (22 male) aged 12-13 took part in 8 focus group discussions. These were transcribed and subjected to deductive thematic analysis to search for themes relating to the prototype willingness model. Participants appeared to make rational decisions about commuting to school or attending sports clubs, but spontaneous choices to be inactive during both break and PE. These reactive decisions seemed influenced by a social context described as more ‘judgmental’ than primary school, characterised by anxiety about physical competence, negative peer evaluation and inactive playground norms. Participants described their images of typical active and inactive adolescents: active images included negative social characteristics including ‘show-off’. There was little concern about the long-term risks of inactivity, although participants seemed to recognise that physical activity is healthy. The Prototype Willingness Model might more fully explain young adolescents’ physical activity in school than rational behavioural models, indicating potential for physical activity interventions that target social anxieties in response to the changing playground environment. Images of active types could be more complex than earlier research has suggested, and their negative characteristics might influence willingness to be active.

Keywords: adolescence, physical activity, prototype willingness model, school

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19502 A Political-Economic Analysis of Next Generation EU Recovery Fund

Authors: Fernando Martín-Espejo, Christophe Crombez

Abstract:

This paper presents a political-economic analysis of the reforms introduced during the coronavirus crisis at the EU level with a special emphasis on the recovery fund Next Generation EU (NGEU). It also introduces a spatial model to evaluate whether the governmental features of the recovery fund can be framed inside the community method. Particularly, by evaluating the brake clause in the NGEU legislation, this paper analyses theoretically the political and legislative implications of the introduction of flexibility clauses in the EU decision-making process.

Keywords: EU, legislative procedures, spatial model, coronavirus

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19501 Warfare Ships at Ancient Egypt: Since Pre-Historic Era (3700 B.C.) Uptill the End of the 2nd Intermediate Period (1550 B.C.)

Authors: Mohsen Negmeddin

Abstract:

Throughout their history, ancient Egyptians had known several kinds and types of boats, which were made from two main kinds of materials, the local one, as the dried papyrus reeds and the local tree trunks, the imported one, as the boats which were made from Lebanon cedar tree trunks. A varied using of these boats, as the fish hunting small boats, the transportation and trade boats "Cargo Boats", as well as the ceremonial boats, and the warfare boats. The research is intending for the last one, the warfare boats and the river/maritime battles since the beginning of ancient Egyptian civilization at the pre-historic era up till the end of the second intermediate period, to reveal the kinds and types of those fighting ships before establishing the Egyptian navy at the beginning of the New Kingdome (1550-1770 B.C). Two methods will follow at this research, the mention of names and titles of these ships through the texts (ancient Egyptian language) resources, and the depiction of it at the scenes.

Keywords: the warfare boats, the maritime battles, the pre-historic era, the second intermediate period

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19500 Framework for Integrating Big Data and Thick Data: Understanding Customers Better

Authors: Nikita Valluri, Vatcharaporn Esichaikul

Abstract:

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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19499 Analysis of Complex Business Negotiations: Contributions from Agency-Theory

Authors: Jan Van Uden

Abstract:

The paper reviews classical agency-theory and its contributions to the analysis of complex business negotiations and gives an approach for the modification of the basic agency-model in order to examine the negotiation specific dimensions of agency-problems. By illustrating fundamental potentials for the modification of agency-theory in context of business negotiations the paper highlights recent empirical research that investigates agent-based negotiations and inter-team constellations. A general theoretical analysis of complex negotiation would be based on a two-level approach. First, the modification of the basic agency-model in order to illustrate the organizational context of business negotiations (i.e., multi-agent issues, common-agencies, multi-period models and the concept of bounded rationality). Second, the application of the modified agency-model on complex business negotiations to identify agency-problems and relating areas of risk in the negotiation process. The paper is placed on the first level of analysis – the modification. The method builds on the one hand on insights from behavior decision research (BRD) and on the other hand on findings from agency-theory as normative directives to the modification of the basic model. Through neoclassical assumptions concerning the fundamental aspects of agency-relationships in business negotiations (i.e., asymmetric information, self-interest, risk preferences and conflict of interests), agency-theory helps to draw solutions on stated worst-case-scenarios taken from the daily negotiation routine. As agency-theory is the only universal approach able to identify trade-offs between certain aspects of economic cooperation, insights obtained provide a deeper understanding of the forces that shape business negotiation complexity. The need for a modification of the basic model is illustrated by highlighting selected issues of business negotiations from agency-theory perspective: Negotiation Teams require a multi-agent approach under the condition that often decision-makers as superior-agents are part of the team. The diversity of competences and decision-making authority is a phenomenon that overrides the assumptions of classical agency-theory and varies greatly in context of certain forms of business negotiations. Further, the basic model is bound to dyadic relationships preceded by the delegation of decision-making authority and builds on a contractual created (vertical) hierarchy. As a result, horizontal dynamics within the negotiation team playing an important role for negotiation success are therefore not considered in the investigation of agency-problems. Also, the trade-off between short-term relationships within the negotiation sphere and the long-term relationships of the corporate sphere calls for a multi-period perspective taking into account the sphere-specific governance-mechanisms already established (i.e., reward and monitoring systems). Within the analysis, the implementation of bounded rationality is closely related to findings from BRD to assess the impact of negotiation behavior on underlying principal-agent-relationships. As empirical findings show, the disclosure and reservation of information to the agent affect his negotiation behavior as well as final negotiation outcomes. Last, in context of business negotiations, asymmetric information is often intended by decision-makers acting as superior-agents or principals which calls for a bilateral risk-approach to agency-relations.

Keywords: business negotiations, agency-theory, negotiation analysis, interteam negotiations

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19498 An Optimal Bayesian Maintenance Policy for a Partially Observable System Subject to Two Failure Modes

Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis, Leila Jafari

Abstract:

In this paper, we present a new maintenance model for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model. A cost-optimal Bayesian control policy is developed for maintaining the system. The control problem is formulated in the semi-Markov decision process framework. An effective computational algorithm is developed and illustrated by a numerical example.

Keywords: partially observable system, hidden Markov model, competing risks, multivariate Bayesian control

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19497 Multi-Criteria Goal Programming Model for Sustainable Development of India

Authors: Irfan Ali, Srikant Gupta, Aquil Ahmed

Abstract:

Every country needs a sustainable development (SD) for its economic growth by forming suitable policies and initiative programs for the development of different sectors of the country. This paper is comprised of modeling and optimization of different sectors of India that form a multi-criterion model. In this paper, we developed a fractional goal programming (FGP) model that helps in providing the efficient allocation of resources simultaneously by achieving the sustainable goals in gross domestic product (GDP), electricity consumption (EC) and greenhouse gasses (GHG) emission by the year 2030. Also, a weighted model of FGP is presented to obtain varying solution according to the priorities set by the policy maker for achieving future goals of GDP growth, EC, and GHG emission. The presented models provide a useful insight to the decision makers for implementing strategies in a different sector.

Keywords: sustainable and economic development, multi-objective fractional programming, fuzzy goal programming, weighted fuzzy goal programming

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19496 Multi-Criteria Decision Making Approaches for Facility Planning Problem Evaluation: A Survey

Authors: Ahmed M. El-Araby, Ibrahim Sabry, Ahmed El-Assal

Abstract:

The relationships between the industrial facilities, the capacity available for these facilities, and the costs involved are the main factors in deciding the correct selection of a facility layout. In general, an issue of facility layout is considered to be an unstructured problem of decision-making. The objective of this work is to provide a survey that describes the techniques by which a facility planning problem can be solved and also the effect of these techniques on the efficiency of the layout. The multi-criteria decision making (MCDM) techniques can be classified according to the previous researches into three categories which are the use of single MCDM, combining two or more MCDM, and the integration of MCDM with another technique such as genetic algorithms (GA). This paper presents a review of different multi-criteria decision making (MCDM) techniques that have been proposed in the literature to pick the most suitable layout design. These methods are particularly suitable to deal with complex situations, including various criteria and conflicting goals which need to be optimized simultaneously.

Keywords: facility layout, MCDM, GA, literature review

Procedia PDF Downloads 207
19495 Two-Warehouse Inventory Model for Deteriorating Items with Inventory-Level-Dependent Demand under Two Dispatching Policies

Authors: Lei Zhao, Zhe Yuan, Wenyue Kuang

Abstract:

This paper studies two-warehouse inventory models for a deteriorating item considering that the demand is influenced by inventory levels. The problem mainly focuses on the optimal order policy and the optimal order cycle with inventory-level-dependent demand in two-warehouse system for retailers. It considers the different deterioration rates and the inventory holding costs in owned warehouse (OW) and rented warehouse (RW), and the conditions of transportation cost, allowed shortage and partial backlogging. Two inventory models are formulated: last-in first-out (LIFO) model and first-in-first-out (FIFO) model based on the policy choices of LIFO and FIFO, and a comparative analysis of LIFO model and FIFO model is made. The study finds that the FIFO policy is more in line with realistic operating conditions. Especially when the inventory holding cost of OW is high, and there is no difference or big difference between deterioration rates of OW and RW, the FIFO policy has better applicability. Meanwhile, this paper considers the differences between the effects of warehouse and shelf inventory levels on demand, and then builds retailers’ inventory decision model and studies the factors of the optimal order quantity, the optimal order cycle and the average inventory cost per unit time. To minimize the average total cost, the optimal dispatching policies are provided for retailers’ decisions.

Keywords: FIFO model, inventory-level-dependent, LIFO model, two-warehouse inventory

Procedia PDF Downloads 279