Search results for: developer decision.

Authors: Mehmet Altınöz

Abstract:

This study focuses on bureau management technologies and information systems in developing countries. Developing countries use such systems which facilitate executive and organizational functions through the utilization of bureau management technologies and provide the executive staff with necessary information. The concepts of data and information differ from each other in developing countries, and thus the concepts of data processing and information processing are different. Symbols represent ideas, objects, figures, letters and numbers. Data processing system is an integrated system which deals with the processing of the data related to the internal and external environment of the organization in order to make decisions, create plans and develop strategies; it goes without saying that this system is composed of both human beings and machines. Information is obtained through the acquisition and the processing of data. On the other hand, data are raw communicative messages. Within this framework, data processing equals to producing plausible information out of raw data. Organizations in developing countries need to obtain information relevant to them because rapid changes in the organizational arena require rapid access to accurate information. The most significant role of the directors and managers who work in the organizational arena is to make decisions. Making a correct decision is possible only when the directors and managers are equipped with sound ideas and appropriate information. Therefore, acquisition, organization and distribution of information gain significance. Today-s organizations make use of computer-assisted “Management Information Systems" in order to obtain and distribute information. Decision Support System which is closely related to practice is an information system that facilitates the director-s task of making decisions. Decision Support System integrates human intelligence, information technology and software in order to solve the complex problems. With the support of the computer technology and software systems, Decision Support System produces information relevant to the decision to be made by the director and provides the executive staff with supportive ideas about the decision. Artificial Intelligence programs which transfer the studies and experiences of the people to the computer are called expert systems. An expert system stores expert information in a limited area and can solve problems by deriving rational consequences. Bureau management technologies and information systems in developing countries create a kind of information society and information economy which make those countries have their places in the global socio-economic structure and which enable them to play a reasonable and fruitful role; therefore it is of crucial importance to make use of information and management technologies in order to work together with innovative and enterprising individuals and it is also significant to create “scientific policies" based on information and technology in the fields of economy, politics, law and culture.

Keywords: Bureau Management, Information Systems.

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Authors: Pablo Cardozo Herrera

Abstract:

In a dynamic market of Information Technology (IT) Service and with high quality demands and high performance requirements in decreasing costs, it is imperative that IT companies invest organizational effort in order to increase the effectiveness of their Information Technology Service Management (ITSM) processes through the improvement of ITSM project management and through solid support to the strategic decision-making process of IT directors. In this article, the author presents an analysis of common issues of IT companies around the world, with strategic needs of information unmet that provoke their ITSM processes and projects management that do not achieve the effectiveness and efficiency expected of their results. In response to the issues raised, the author proposes a framework consisting of an innovative theoretical framework model of ITSM management and a technological solution aligned to the Information Technology Infrastructure Library (ITIL) good practices guidance and ISO/IEC 20000-1 requirements. The article describes a research that proves the proposed framework is able to integrate, manage and coordinate in a holistic way, measurable and auditable, all ITSM processes and projects of IT organization and utilize the effectiveness assessment achieved for their strategic decision-making process increasing the process maturity level and improving the capacity of an efficient management.

Keywords: Innovation in IT services, ITSM processes, ITIL and ISO/IEC 20000-1, IT service management, IT service excellence.

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Authors: Ali Payan, Bijan Rahmani Parchicolaie

Abstract:

Universities have different offices such as educational, research, student, administrative, and financial offices. This paper considers universities as groups of decision making units (DMUs) in which DMUs are their offices. This approach gives us with a more just evaluation of universities instead of separate evaluation of the offices of universities. The proposed approach to evaluate group performance of universities is based on common set of weights method in DEA. The suggested method not only can compare groups and measure their efficiencies, but also can calculate the efficiency of units within group and efficiency spread of groups. At last, the suggested method is applied for the analysis of the performance of universities in 14^th district of Islamic Azad University as groups under evaluation.

Keywords: Common set of weights, group efficiency, performance analysis, spread efficiency.

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: Data mining, digital libraries, digital preservation, file format.

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Authors: Nikhil Kewal Krishna Mehta

Abstract:

In the past researchers have questioned the effectiveness of ethics training in higher education. Also, there are observations that support the view that ethical behaviour (range of actions)/ethical decision making models used in the past make use of vignettes to explain ethical behaviour. The understanding remains in the perspective that these vignettes play a limited role in determining individual intentions and not actions. Some authors have also agreed that there are possibilities of differences in one’s intentions and actions. This paper makes an attempt to fill those gaps by evaluating real actions rather than intentions. In a way this study suggests the use of an experiential methodology to explore Berlo’s model of communication as an action along with orchestration of various principles. To this endeavor, an attempt was made to use conversational analysis in the pursuance of evaluating ethical decision making behaviour among students and middle level managers. The process was repeated six times with the set of an average of 15 participants. Similarities have been observed in the behaviour of students and middle level managers that calls for understanding that both the groups of individuals have no cognizance of their actual actions. The deliberations derived out of conversation were taken a step forward for meta-ethical evaluations to portray a clear picture of ethical behaviour among participants. This study provides insights for understanding demonstrated unconscious human behaviour which may fortuitously be termed both ethical and unethical.

Keywords: Berlo’s action model of communication, Conversational Analysis, Ethical behaviour, Ethical decision making, experiential learning, Intentions and Actions.

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Authors: Cory Cannon

Abstract:

In the current era of shrinking budgets, increasing amounts of worldwide natural disasters, state and non-state initiated conflicts within the world. The response has involved multinational coalitions to conduct effective military operations. The need for a Knowledge Management strategy when developing these coalitions have been overlooked in the past and the need for developing these accords early on will save time and help shape the way information and knowledge are transferred from the staff and action officers of the coalition to the decision-makers in order to make timely decisions within an ever changing environment. The aim of this paper is to show how Knowledge Management has developed within the United States military and how the transformation of working within a Combined/ Joint environment in both the Middle East and the Far East has improved relations between members of the coalitions as well as being more effective as a military force. These same principles could be applied to multinational corporations when dealing with cultures and decision-making processes.

Keywords: Civil-military, culture, joint environment, knowledge management.

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Authors: Y. O’Connor, C. Heavin, S. O’ Connor, J. Gallagher, J. Wu, J. O’Donoghue

Abstract:

Background: To improve the delivery of paediatric healthcare in low resource settings, Community Health Workers (CHW) have been provided with a paper-based set of protocols known as Community Case Management (CCM). Yet research has shown that CHW adherence to CCM guidelines is poor, ultimately impacting health service delivery. Digitising the CCM guidelines via mobile technology is argued in extant literature to improve CHW adherence. However, little research exist which outlines how (a) this process can be digitised and (b) adherence could be improved as a result. Aim: To explore how an electronic mobile version of CCM (eCCM) can overcome issues associated with the paper-based CCM protocol (inadequate adherence to guidelines) vis-à-vis service blueprinting. This service blueprint will outline how (a) the CCM process can be digitised using mobile Clinical Decision Support Systems software to support clinical decision-making and (b) adherence can be improved as a result. Method: Development of a single service blueprint for a standalone application which visually depicts the service processes (eCCM) when supporting the CHWs, using an application known as Supporting LIFE (SL eCCM app) as an exemplar. Results: A service blueprint is developed which illustrates how the SL eCCM app can be utilised by CHWs to assist with the delivery of healthcare services to children. Leveraging smartphone technologies can (a) provide CHWs with just-in-time data to assist with their decision making at the point-of-care and (b) improve CHW adherence to CCM guidelines. Conclusions: The development of the eCCM opens up opportunities for the CHWs to leverage the inherent benefit of mobile devices to assist them with health service delivery in rural settings. To ensure that benefits are achieved, it is imperative to comprehend the functionality and form of the eCCM service process. By creating such a service blueprint for an eCCM approach, CHWs are provided with a clear picture regarding the role of the eCCM solution, often resulting in buy-in from the end-users.

Keywords: Adherence, community health workers, developing countries, mobile clinical decision support systems, CDSS, service blueprint.

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Authors: Jaouad Oukrich, Belaid Bouikhalene, Noureddine Askour

Abstract:

This paper deals with the problem of management of information resources in libraries of the public institution Sultan Moulay Slimane University (SMSU) in order to analyze the satisfaction of the readers, and allow university leaders to make better strategic and instant decisions. For this, the integration of an integrated management decision library system is a priority program of higher education, as part of the Digital Morocco, which has a proactive policy to develop the use of new technologies information and communication in higher institutions. This operational information system can provide better services to the students and for the leaders. Our approach is to integrate the tools of business intelligence (BI) in the library management by using power BI.

Keywords: PMB, integrated library management system, ILMS, document, SMSU, power BI, satisfaction.

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Authors: C. Ardil

Abstract:

This article presents a multiple criteria evaluation for a trainer aircraft selection problem using "preference analysis for reference ideal solution (PARIS)” approach. The available relevant literature points to the use of multiple criteria decision making analysis (MCDMA) methods for the problem of trainer aircraft selection, which often involves conflicting multiple criteria. Therefore, this MCDMA study aims to propose a robust systematic integrated framework focusing on the trainer aircraft selection problem. For this purpose, an integrated preference analysis approach based the mean weight and entropy weight procedures with PARIS, and TOPSIS was used for a MCDMA compensating solution. In this study, six trainer aircraft alternatives were evaluated according to six technical decision criteria, and data were collected from the current relevant literature. As a result, the King Air C90GTi alternative was identified as the most suitable trainer aircraft alternative. In order to verify the stability and accuracy of the results obtained, comparisons were made with existing MCDMA methods during the sensitivity and validity analysis process.The results of the application were further validated by applying the comparative analysis-based PARIS, and TOPSIS method. The proposed integrated MCDMA systematic structure is also expected to address the issues encountered in the aircraft selection process. Finally, the analysis results obtained show that the proposed MCDMA method is an effective and accurate tool that can help analysts make better decisions.

Keywords: aircraft, trainer aircraft selection, multiple criteria decision making, multiple criteria decision making analysis, mean weight, entropy weight, MCDMA, PARIS, TOPSIS

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Authors: Vichai Rungreunganaun, Chirawat Woarawichai

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The objective of this research is to calculate the optimal inventory lot-sizing for each supplier and minimize the total inventory cost which includes joint purchase cost of the products, transaction cost for the suppliers, and holding cost for remaining inventory. Genetic algorithms (GAs) are applied to the multi-product and multi-period inventory lot-sizing problems with supplier selection under storage space. Also a maximum storage space for the decision maker in each period is considered. The decision maker needs to determine what products to order in what quantities with which suppliers in which periods. It is assumed that demand of multiple products is known over a planning horizon. The problem is formulated as a mixed integer programming and is solved with the GAs. The detailed computation results are presented.

Keywords: Genetic Algorithms, Inventory lot-sizing, Supplier selection, Storage space.

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Authors: Namal A. Senanayake, A. Beg, Withana C. Prasad

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This paper analyzes the patterns of the Monte Carlo data for a large number of variables and minterms, in order to characterize the circuit path length behavior. We propose models that are determined by training process of shortest path length derived from a wide range of binary decision diagram (BDD) simulations. The creation of the model was done use of feed forward neural network (NN) modeling methodology. Experimental results for ISCAS benchmark circuits show an RMS error of 0.102 for the shortest path length complexity estimation predicted by the NN model (NNM). Use of such a model can help reduce the time complexity of very large scale integrated (VLSI) circuitries and related computer-aided design (CAD) tools that use BDDs.

Keywords: Monte Carlo data, Binary decision diagrams, Neural network modeling, Shortest path length estimation.

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

Abstract:

This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.

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Authors: Insung Jung, Gi-Nam Wang

Abstract:

In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Shahzadah Fahad Qureshi, Jianqing Zhang

Abstract:

The wisest economic decision of United States in the 20th century was establishing the favorable international monetary system, and capturing the leadership position in it. This decision gave economic hegemony to the US for the next more than 7 decades. The continuation of this hegemony till the next decade seems difficult as the US economy is under continuous streams of recessions since 2007. On the other hand, Chinese economy is progressing with a very fast speed and is estimated to pass the US economy till 2025, in various aspects. Will the US be able to continue its leadership in the IMS? Will China replace US in the international monetary system? The answers to these questions have been explored by comparing the economic competitiveness of US and China, with respect to each other. The paper concludes that the change in global economic environment will compel US to share the leadership of international monetary system with China. This sharing will solve most problems of the current IMS, but will also birth some new problems.

Keywords: Economic competitiveness, Global economic environment (GEE), International monetary fund (IMF), International monetary system (IMS)

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Authors: S. Turkan

Abstract:

In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: Data envelopment analysis, super efficiency, financial ratios, BCC model.

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Authors: Amit Kumar, Pushpinder Singh, Parampreet Kaur, Amarpreet Kaur

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Ranking of fuzzy numbers play an important role in decision making, optimization, forecasting etc. Fuzzy numbers must be ranked before an action is taken by a decision maker. In this paper, with the help of several counter examples it is proved that ranking method proposed by Chen and Chen (Expert Systems with Applications 36 (2009) 6833-6842) is incorrect. The main aim of this paper is to propose a new approach for the ranking of generalized trapezoidal fuzzy numbers. The main advantage of the proposed approach is that the proposed approach provide the correct ordering of generalized and normal trapezoidal fuzzy numbers and also the proposed approach is very simple and easy to apply in the real life problems. It is shown that proposed ranking function satisfies all the reasonable properties of fuzzy quantities proposed by Wang and Kerre (Fuzzy Sets and Systems 118 (2001) 375-385).

Keywords: Ranking function, Generalized trapezoidal fuzzy numbers

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Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

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Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, FAHP, TOPSIS, PROMETHEE, decision support system.

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Authors: K. Aravindhan, Trishit Bandyopadhyay, Mahesh Mehendale, Supriya Kumar De

Abstract:

The inherent iterative nature of product design and development poses significant challenge to reduce the product design and development time (PD). In order to shorten the time to market, organizations have adopted concurrent development where multiple specialized tasks and design activities are carried out in parallel. Iterative nature of work coupled with the overlap of activities can result in unpredictable time to completion and significant rework. Many of the products have missed the time to market window due to unanticipated or rather unplanned iteration and rework. The iterative and often overlapped processes introduce greater amounts of ambiguity in design and development, where the traditional methods and tools of project management provide less value. In this context, identifying critical metrics to understand the iteration probability is an open research area where significant contribution can be made given that iteration has been the key driver of cost and schedule risk in PD projects. Two important questions that the proposed study attempts to address are: Can we predict and identify the number of iterations in a product development flow? Can we provide managerial insights for a better control over iteration? The proposal introduces the concept of decision points and using this concept intends to develop metrics that can provide managerial insights into iteration predictability. By characterizing the product development flow as a network of decision points, the proposed research intends to delve further into iteration probability and attempts to provide more clarity.

Keywords: Decision Points, Iteration, Product Design, Rework.

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Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami

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Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

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Authors: Chen Wu, Lijuan Wang

Abstract:

Relation between tolerance class and indispensable attribute and knowledge dependency in rough set model with tolerance relation is explored. After giving definitions and concepts of knowledge dependency and knowledge dependency degree for incomplete information system in tolerance rough set model by distinguishing decision attribute containing missing attribute value or not, the result of maintaining reflectivity, transitivity, augmentation, decomposition law and merge law for complete knowledge dependency is proved. Knowledge dependency degrees (not complete knowledge dependency degrees) only satisfy some laws after transitivity, augmentation and decomposition operations. An algorithm to solve attribute reduction in an incomplete decision table is designed. The correctness is checked by an example.

Keywords: Incomplete information system, rough set, tolerance relation, knowledge dependence, attribute reduction.

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Authors: Indradip Banerjee, Souvik Bhattacharyya, Gautam Sanyal

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‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.

Keywords: Steganalysis, Moments, Wavelet Domain, KNN, K*, LWL, Naive Bayes Classifier, Neural networks, Decision trees, SVM.

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Authors: S. Kotsiantis, E. Koumanakos, D. Tzelepis, V. Tampakas

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This paper explores the effectiveness of machine learning techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. To this end, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 164 fraud and non-fraud Greek firms in the recent period 2001-2002. The decision of which particular method to choose is a complicated problem. A good alternative to choosing only one method is to create a hybrid forecasting system incorporating a number of possible solution methods as components (an ensemble of classifiers). For this purpose, we have implemented a hybrid decision support system that combines the representative algorithms using a stacking variant methodology and achieves better performance than any examined simple and ensemble method. To sum up, this study indicates that the investigation of financial information can be used in the identification of FFS and underline the importance of financial ratios.

Keywords: Machine learning, stacking, classifier.

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Authors: Ezeni Brzovska, Durdana Ozretic-Dosen

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The purpose of this paper is to deepen the understanding of the product cues that influence purchase decision for a specific product category – chocolate, and to identify demographic differences in the buying behavior. ANOVA was employed for analyzing the significance level for nine product cues, and the survey showed statistically significant differences among different age and gender groups, and between respondents with different levels of education. From the theoretical perspective, the study adds to the existing knowledge by contributing with the research results from the new environment (Southeast Europe, Macedonia), which has been neglected so far. Establishing the level of significance for the product cues that affect buying behavior in the chocolate consumption context might help managers to improve marketing decision-making, and better meet consumer needs through identifying opportunities for packaging innovations and/or personalization toward different target groups.

Keywords: Chocolate consumption context, chocolate selection, demographic characteristics, product cues.

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Authors: Michael Grigutsch, Marco Kennemann, Peter Nyhuis

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Due to the recovering global economy, enterprises are increasingly focusing on logistics. Investing in logistic measures for a production generates a large potential for achieving a good starting point within a competitive field. Unlike during the global economic crisis, enterprises are now challenged with investing available capital to maximize profits. In order to be able to create an informed and quantifiably comprehensible basis for a decision, enterprises need an adequate model for logistically and monetarily evaluating measures in production. The Collaborate Research Centre 489 (SFB 489) at the Institute for Production Systems (IFA) developed a Logistic Information System which provides support in making decisions and is designed specifically for the forging industry. The aim of a project that has been applied for is to now transfer this process in order to develop a universal approach to logistically and monetarily evaluate measures in production.

Keywords: Measures in Production, Logistic Operating Curves, Transfer Functions, Production Logistics

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Authors: P. Beraldi, M. E. Bruni

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Data Envelopment Analysis (DEA) is one of the most widely used technique for evaluating the relative efficiency of a set of homogeneous decision making units. Traditionally, it assumes that input and output variables are known in advance, ignoring the critical issue of data uncertainty. In this paper, we deal with the problem of efficiency evaluation under uncertain conditions by adopting the general framework of the stochastic programming. We assume that output parameters are represented by discretely distributed random variables and we propose two different models defined according to a neutral and risk-averse perspective. The models have been validated by considering a real case study concerning the evaluation of the technical efficiency of a sample of individual firms operating in the Italian leather manufacturing industry. Our findings show the validity of the proposed approach as ex-ante evaluation technique by providing the decision maker with useful insights depending on his risk aversion degree.

Keywords: DEA, Stochastic Programming, Ex-ante evaluation technique, Conditional Value at Risk.

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: Discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability.

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Authors: Gülfem Alptekin, S. Emre Alptekin

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Global competitiveness has recently become the biggest concern of both manufacturing and service companies. Electronic commerce, as a key technology enables the firms to reach all the potential consumers from all over the world. In this study, we have presented commonly used electronic payment systems, and then we have shown the evaluation of these systems in respect to different criteria. The payment systems which are included in this research are the credit card, the virtual credit card, the electronic money, the mobile payment, the credit transfer and the debit instruments. We have realized a systematic comparison of these systems in respect to three main criteria: Technical, economical and social. We have conducted a fuzzy multi-criteria decision making procedure to deal with the multi-attribute nature of the problem. The subjectiveness and imprecision of the evaluation process are modeled using triangular fuzzy numbers.

Keywords: Electronic payment systems, fuzzy multi-criteriadecision making, analytical hierarchy process.

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Authors: Michael T. Miller, G. David Gearhart

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Shared governance is an important element in higher education decision making. Through the joint decision making process, faculty members are provided an opportunity to help shape the future of an institution while increasing support for decisions that are made. Presidents, those leaders who are legally bound to guide their institutions, must find ways to collaborate effectively with faculty members in making decisions, and the first step in this process is understanding when and how presidents and faculty leaders interact. In the current study, a national sample of college presidents reported their preparation for the presidency, their perceptions of the functions of a faculty senate, and ultimately, the locations for important interactions between presidents and faculty senates. Results indicated that presidents, regardless of their preparation, found official functions to be the most important for communicating, although, those presidents with academic backgrounds were more likely to perceive faculty senates as having a role in all aspects of an institutions management.

Keywords: College faculty, college president, faculty senate, leadership.

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Authors: P.Cordero, R.Poler, R.Sanchis

Abstract:

The environmental impacts caused by the current production and consumption models, together with the impact that the current economic crisis, bring necessary changes in the European industry toward new business models based on sustainability issues that could allow them to innovate and improve their competitiveness. This paper analyzes the key environmental issues and the current and future market trends in one of the most important industrial sectors in Spain, the furniture sector. It also proposes new decision support tools -diagnostic kit, roadmap and guidelines- to guide companies to implement sustainability criteria into their organizations, including eco-design strategies and other economical and social strategies in accordance with the sustainability definition, and other available tools such as eco-labels, environmental management systems, etc., and to use and combine them to obtain the results the company expects to help improve its competitiveness.

Keywords: Furniture sector, eco-design, sustainability, economical crisis, market trends, roadmap

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Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

Abstract:

Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: Additive manufacturing, decision-makings, environmental impact, predictive models.

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