Graduate School of Natural and Applied Sciences
Permanent URI for this community
Browse
Browsing Graduate School of Natural and Applied Sciences by Subject "industrial engineering"
Now showing 1 - 20 of 21
Results Per Page
Sort Options
Item AN ERGONOMIC STUDY BRIDGING NORTH CYPRUS INDUSTRIAL DISTRICT WORK PLACES AND DOMESTIC HAZARDS(2017-06-02) KHASHEI, BARQ RAAD; ERKAN, Turan ErmanThis research work seek to present a research undertaken in North Cyprus (Lefkosa Industrial zone ) as regards health and safety issues – using the knowledge and practice acquired from workplace to solve domestic hazards. Seven research questions were put up and 3 hypothesis were constructed to be tested in this research work in which this research work provided answers to. In the findings of this research work, it was discovered that health and safety trainings that the respondents were exposed to were useful and applicable to solving health and safety issues in homes but it did not simply meant that the homes were totally safe from domestic hazards. This research work is a case study and it is pregnant with its own limitations in which time, small sample size and a specific location were the restraint.Item ARTIFICIAL NEURAL NETWORK BASED DECISIVE PREDICTION MODELS ON HIGH FREQUENCY FINANCIAL DATA(2017-01-07) Karaçor, Adil Gürsel; Erkan, Turan ErmanHigh frequency financial data are somewhat hard to model or predict, if not totally impossible, as stochastic processes and many other random factors are involved. In this thesis; a novel Artificial Intelligence model is designed and developed for financial time series prediction and decision making. Possibility to enhance prediction accuracy for foreign exchange rates is investigated in two ways: first applying an outside the box approach by bringing about methodology and techniques to facilitate the use of predictive models in engineering design to model price graphs by exploiting their visual properties together with principles of chaos theory, and secondly employing the most efficient methods to detect patterns to classify the direction of movement. The approach that exploits the visual properties of price graphs makes use of density regions along with high and low values describing the shape just as in Machine Vision. Mainly Artificial Neural Networks are used in modeling. However, other state-of-the-art methods; Extreme Gradient Boosting and Support Vector Machine are too used for comparison. The designed system is also software coded as a real-time trading robot. Comparable prediction results and profits are achieved in tests and simulations.Item COMPARISON AND ASSESSMENT OF SHRINKAGE METHODS IN CASE OF MULTICOLLINEARITY PROBLEM(2022-06-14) KILIÇOĞLU, Şevval; YERLİKAYA ÖZKURT, FatmaThe use of data analysis and data interpretation are increasing in importance in many fields of applied science such as engineering, medicine, natural and social sciences. For this purposes, statistical methods are used to collect, analyze and interpret data. Among the statistical analysis methods, one of the most preferred one is multiple linear regression due to its simplicity and interpretation. It describes the relationship between more than one independent variables and a dependent variable. However, sometimes, it can be observed that there is a multicollinearity (linear relationship) between the independent variables in data sets to which multiple linear regression models will be applied. This causes the variance of the estimated coefficients in the model to be large and their biases to be low, and in such cases, model predictions may not give accurate results and the reliability of the model may decrease. If there is a multicollinearity between the variables in the data set, it is of great importance to determine this in advance. For this purpose, there are many multicollinearity determination method and there are several methods developed to solve this problem. The most popular and powerful methods to handle this problem are shrinkage methods. Shrinkage methods aim to minimize the multicollinearity problem by reducing the variance of the estimated parameters in the model. Ridge Regression, Lasso, and Elastic Net are the most preferred shrinkage methods that set the coefficients of the variables in the model to zero or very close to zero. In this thesis, Ridge Regression, Lasso, and Elastic Net were applied to nine different simulated data sets with different characteristics. The Copula function was used to create multicollinearity between independent variables for simulated data sets. Following that, all of the aforementioned shrinkage methods were also applied on three real-world data sets. These data sets were matched with the simulated data sets based on their sizes, which were classified as small, medium, and large. For the simulated data sets, a 10-fold Cross-Validation (CV) approach is applied to validate the shrinkage methods. On the other hand, the hold-out method, which relies on only one training and test split, is preferred for real-world data sets. After all models were created, well-known performance measures were calculated for each method to determine which method gives better results in the data set in which characteristics. Mean squared error (MSE), mean squared error based on number of independent variables (PMSE), R-squared, mean absolute error (MAE) and explained variance are the performance measures used in decision making. Based on performance results, the methods were compared with TOPSIS, which is one of the multi-criteria decision making methods, and the order of preference was determined for each data set. When all the performance and TOPSIS results are examined, it is seen that generally ridge regression gives the best results in small data sets, as the data set grows, that is, as the complexity increases, shrinkage methods tend to make variable selection to reduce the variance of the estimated coefficients, and therefore lasso or elastic net models give better results. If a general ranking is made among the models, they can be listed as lasso, elastic net and ridge regression.Item DETERMINATION OF KEY PERFORMANCE INDICATORS FOR MEASURING LIBYAN AIRPORTS SUCCESS(2017-06-02) Eshtaiwi, Mohamed; Erkan, Turan ErmanAn airport is one of the most important modes of transportation and they have a large effect on local, regional, and national economies. According to several recent studies, the global air traffic density has registered rapid growth in recent years. Therefore, performance measurements in airport settings have been of paramount importance both in Libya and worldwide. This thesis proposes a framework to help decision makers in the Libyan airport industry with performance upgrades. The goals of this study are twofold: First, to develop a set of essential airport key performance indicators (KPIs) in five aspects of airport performance based on previous studies to help airport authorities in Libya with effective decisions regarding airport performance. Then, the AHP method is applied to determine KPI weights by summarizing the opinions of experts. Second, it provides a performance comparison between the three international airports in Libya (MJI, MRA, and LAQ) based on the comparison judgments of experts by using two different multi-criteria decision-making methods, namely AHP and Grey Theory. The results of this study have identified 17 Key Performance Indicators (KPIs) in five activity areas that, in their view, are the most important airport performance indicators in the present case study. The results also showed that MRA Airport performed better than the other two airports. MJI Airport ranked next followed by LAQ.Item DEVELOPMENT OF DECISION SUPPORT MODEL FOR SELECTING AN EQUIPMENT MAINTENANCE PLAN USING A FUZZY MCDM APPROACH(2022-01-26) ABDULGADER, Fathia Sghayer; Erdebilli, BabekIn complex decision making, using multi-criteria decision making (MCDM) methodologies is the most scientific way to ensure an informed and justified decision between several alternatives. MCDM’s have been used in different ways and with several applications that proved their efficiency in achieving this goal. In this research, the advantages and disadvantages of the different MCDM methodologies are studied, along with the different techniques implemented to increase their accuracy and precision. The main aim of the study is to develop a hybrid MCDM process that combines the strengths of several MCDM methods and apply it to choose the best fit maintenance policy/ strategy for industrial application. Moreover, fuzzy linguistic terms are utilized in all of the used MCDM techniques in order to eliminate the uncertainty and ambiguity of the results. Through an extensive literature review performed on studies that have used MCDM methods in a hybrid context and using fuzzy linguistic terms, a model is developed to use fuzzy DEMATEL-AHP-TOPSIS hybrid technique. The model with its application is the first of its kind, which combines the strengths of fuzzy DEMATEL in establishing interrelationships between the several criteria, as well as performing a pairwise comparison between the criteria for prioritization using the fuzzy AHP method. Thereafter, the alternatives are compared using fuzzy TOPSIS method by establishing negative and positive solutions and calculating the relative closeness for each of the alternatives. Furthermore, six main criteria, twenty-four sub criteria, and five alternatives are selected from the literature for the model application. The findings of the research show that predictive maintenance is the best choice as a maintenance plan, followed closely by preventive maintenance. The results of the research confirmed the success of the developed model to select maintenance plans based on experts’ inputs and using the developed fuzzy MCDM approach.Item DEVELOPMENT OF EFFECTIVE METHODOLOGY FOR IMPROVING UNDERGRADUATE PROGRAM CURRICULUM IN HIGHER EDUCATION UTILIZING SIX SIGMA APPROACH(2022-02-15) Dakhil, Abdulmuhsen; Özkil, AltanThe curriculum structure of undergraduate programs in all universities is based on the required knowledge, skills, and attitudes needed in business life by graduates of related department. Graduates will use their knowledge, skills, and competencies to fulfill the requirements of jobs related with selected department. However, there is a general concern that the existing undergraduate programs of universities are not providing graduates with the required level of knowledge, skills, and attitudes that they will need in order to succeed in professional practice. This simply shows the gap between what is taught in university and what is needed in industry. For that reason, a considerable number of graduates are employed in the industrial environment where there isn’t often close match between the elements of their education, and the skills and knowledge required for the success in the industry. As a result, the academia has been attempting to improve curricula for many years. Some new courses are added, some of current courses are deleted, and some of the current courses are combined. A remarkable amount of research has been conducted on curriculum development. What is lacking, a methodology that incorporates the many dimensions that affecting the process of curriculum improvement as well as quantitative tools that address the requirements of the various stakeholders that are essential to improving the curriculum. The aim of this study is developing a quantitative methodology utilizing Six-Sigma quality improvement approach to make the changes required for improving undergraduate program curriculum of higher education institutions. The changes needed for improving the curriculum can be identified in terms of knowledge, skills, and competencies that graduate from a particular program curriculum need to possess by implementing this methodology. The developed methodology was implemented to make improvement in one of the engineering departments in higher education. Manufacturing engineering department was selected for this purpose. A set of desired competencies were developed from the exiting data related to manufacturing engineering programs. This set is then used in the development of a comprehensive survey to capture different perspectives from various stakeholders such as graduates, employers, and academics. Statistical analysis of the survey was done by SPSS to get some information about the importance and their roles in the performance of developed competencies to identify where improvement efforts to be targeted. Some changes to the current curriculum of the manufacturing engineering department were proposed by using the developed methodology. Proposed changes were verified by using commercial recruitment adds for the manufacturing engineering department in kariyer.net.Item EVALUATION OF THE CUSTOMER RELATIONSHIP MANAGEMENT(CRM) CONSULTANT PERFORMANCE BY USING SWARA AND WASPAS METHODS(2022-01-24) Çalkın, Şuayip; ERKAN, Turan ErmanCustomer relationship management (CRM) implementation is a very prior decision for companies to increase customer-related revenue or customer lifecycle. The implementation process involves many problems, therefore, most of the companies would prefer to benefit from the CRM consultant’s experience. However, Pries & Stone, 2004 theory have shown that consultancy does not make everything right. At this point, the most significant questions are how can we choose the right CRM consultant and measure their performance? These questions become a crucial decision for both firms and consultant companies. In this thesis, one of the popular Multi Criteria decision-making (MCDM) methodsthat is Weighted Aggregates Sum Product Assessment (WASPAS) is used for ranking the performance of Customer Relationship Management (CRM) Consultant. Step-wise Weight Assessment Ratio Analysis (SWARA) method is utilized for finding the weight of criteria. This research aims to create an awareness of the role of CRM consultants and adds the sample application of MCDM in literature for especially CRM consultancy firms.Item INTEGRATING LEAN SIX SIGMA WITH AGILE SOFTWARE DEVELOPMENT METHODOLOGY(2022-02-16) Badwe, Safia; ERKAN, Turan ErmanIn the last two decades, the Six Sigma approach has also experienced extended introduction into the software development industry, with lean thinking emerging as a new paradigm to make the process more efficient. Some software companies have been trying to adapt Six Sigma and Lean for their business and development initiatives. Lean Six Sigma (LSS) accelerates the test and reconciliation aspects of item advancement and makes room for providing top-notch products to purchasers. Still, a need for constant change and transformation has forced organizations into adopting to complex and new working environments, resulting in software development methodologies to become a framework for planning and coordinating programs and communicating with customers so as to collect the requirements. In this respect, LSS and Agile methodologies are regarded as a set of development initiatives to satisfy such demands at an early stage and incorporate high-quality changes into the software development process; hence the present study explores the relationship between the methodologies mentioned above in software development. This research presents the results from a theoretical and empirical part. The first part is to introduce a model that combines the operational stages to examine Six Sigma, Lean, Lean Six Sigma, Agile and Scrum methodologies to try and devise a new approach called ‗LSS-Agile‘ methodology. The second part presents the results of a survey study conducted with practitioners of software development companies in Turkey and abroad. The questionnaire focuses on several aspects, most importantly: benefits implementation, critical success factors, satisfaction, change requirements, experiences, and problems faced when using methodologies. The empirical perspective is analyzed by developing hypotheses about the concepts and factors on the study of methodologies and their impact on software development. The results highlight the most important factors leading to the success and failure of software development as well as the most beneficial aspects of the performance of methodologies. To this end, the analysis of the Lean Six Sigma and Agile methodology, their interrelationships helps to better understand the idea of integrating the two. As a comparisons carried out between a number of Turkish and Canadian companies specializing in this field, the results confirm that Turkish companies in the software development sector entered the world market from the widest successfully and have become one of the most competitive countries in this field.Item LOAD DEMAND FORECASTING USING ARTIFICIAL NEURAL NETWORKS AND FUZZY LOGIC METHODS(2022-05-12) AL-ANI, BARQ RAAD KHASHEI; ERKAN, Turan ErmanThis study proposes using artificial neural networks (ANNs) and fuzzy logic (FL) to estimate load demand data to forecast hourly electricity loads in Turkey or 2017 and 2018. We used Real Time Consumption as hourly electric load based on EPİAŞ data for 2017 to 2018. The load forecast was actualized using two machine learning techniques: ANN and fuzzy logic FL. The predicted data was compared to the actual data by plotting on a graph. This study used the ANN and FL methods to optimise the demand for load forecast in Turkey's power systems. The first and last 200 hours were plotted on ANN to get a better visualisation pattern, and the overall estimated hourly load for Turkey was calculated by adding the hourly estimations from each area. The minimum and maximum readings for the year 2017 are 18851.35 MWh and 47062.40 MWh whereas the mean and standard deviation readings are 33102.19 Mwh and 4968.67 MWh. As a result, the comparison of these models was used to forecast the load, all of which have different load patterns and origins. The series are stationary across the year and it peaks during the month of August. The MAPE values for FL for 2017 and 2018 are 3.7986094 and 5.28635983 respectively which is very good and falls in high accurate forecasting results. It can be concluded that the FL gives a better prediction than the ANN for both years. Electrical peak reduction is a vital component of any plan for managing energy demand, and forecasting electric load assists in planning peak load demand reductions to meet energy demand management targets. It can be concluded that the FL gives us a better prediction than the ANN for both years. Home, energy management research will benefit from the new load forecasting models proposed in this study.Item MOBILE CUSTOMER RELATIONSHIP MANAGEMENT: A TOOL TO CREATE COMPETITIVE ADVANTAGE WITHIN CONSTRUCTION COMPANIES IN NIGERIA(2017-06-02) Almakura, Faisal Ahmed; Erkan, ErmanThe arrival of IT technology especially in mobile devices has forced most companies to re-think and re-evaluate the way they interact, relate and communicate with their customers. In the early 1990s, many organizations understood that business should be followed with a more customer centric approach using strategies like the Customer Relationship Management (CRM). Nevertheless, the rapid evolution of technology has caused many organizations to find new and alternative ways of managing their relationships with their customers. These new ways have given birth to other approaches like the Mobile Customer Relationship Management (mCRM). This thesis studies why there is no proper implementation of mCRM in construction companies in Nigeria, and the factors that hinder this proper implementation and it puts these factors into ranks using Analytical Hierarchy Process (AHP). The thesis pays close attention to the relationships within the Government-To-Business (G2B) and Business-To-Business (B2B) companies. There are so many contractor companies in Nigeria and there are more that are opening, as Nigeria is a fast developing country, this fact necessitates this study. The study, which is divided with primary goals and secondary goals, was achieved using two different research approaches, the qualitative and the quantitative approaches. The qualitative approach was done by a questionnaire that was answered by two highly qualified participants from two different companies. And the quantitative approach was done also using questionnaires that was answered by 38 qualified participants, and with the data obtained from their answers a Multi Criteria Decision Making (MCDM) technique was applied.Item MULTIMODAL TRANSPORTATION OPTIMIZATION OF MULTI-COMMODITY HAZARDOUS MATERIALS WITH A LEXICOGRAPHIC GOAL PROGRAMMING MODEL(2022-06-22) GÜZEY, Refika Ruzin; BAÇ, UğurThere are many hazardous materials defined in different classes with their chemical and physical properties, and they are used as raw materials in many products produced in the production sector. Those who use and transport these substances should aim at the minimum risk that ensures the implementation of legal rules, in addition to the objectives such as the minimum cost and time stipulated in their businesses. Highway is widely used for hazardous materials in our country. In the literature, the efficiency of different types of multimodal transport has been mentioned. There are multi objective studies, mainly with minimum cost and minimum risk, in which multi-modal transportation is used for the transportation of hazardous materials. These studies mostly focused on the fuel group, which is one of the hazardous materials. In this study, minimizing the cost, risk and ultimately the transportation time in transportation between the hazardous materials producers and the needy people in different cities are discussed. In addition, it has been evaluated that air transportation, which does not have a priority of use, is an option for the multi-modal transportation of hazardous materials that are outside the fuel group and can be transported by plane. Goal programming model is used to solve the problem. The effectiveness of the proposed model was evaluated by coding in the CPLEX solver with a case study.Item PERFORMANCE MEASUREMENT AND IMPROVEMENT IN CONSTRUCTION INDUSTRY: “AN APPLICATION OF TURKEY CASE”(2017-01-04) Tuncer, Veysel Emre; Erkan, Turan ErmanThis thesis reviews the performance evaluation and improvement in construction industry. A balanced scorecard framework is proposed for performance measurement in Turkish Construction Industry. In addition, two mixed integer mathematical programming models are developed for performance improvement.Item RELIABILITY CHARACTERISTICS OF A RENEWABLE HYBRID ENERGY SYSTEM(2022-01-11) ÖZDEMİR, İREM BULANIK; Eryılmaz, Serkan; Devrim, YılmazRenewable energy is one of the rising trends of the modern world due to its eco friendly nature, its inexhaustibility, low-cost energy supply, and wide usage areas. The most important disadvantage, the inability to provide uninterrupted energy, has led the world to hybrid renewable energy systems. These systems are composed of two or more renewable energy components that complement each other and aim to close each other's weaknesses. In this thesis, a model including wind turbine (WT), solar panel (PV) and Proton Exchange Membrane Fuel Cell (PEMFC) was developed and analyzed in reliability point of view. To this end, first the probability distribution of the aggregate power produced by wind turbines and solar panels was derived theoretically. In the application part, wind speed and solar irradiation data were collected from the meteorology station established at Atilim University İncek Campus. One of the most essential part of the thesis is reliability based evaluations of power systems. Loss of Load Probability (LOLP), Loss of Load Expectation (LOLE), Energy Expected Not Supplied (EENS), and Energy Index of Reliability (EIR) were calculated for the hybrid system under concern.Item SELECTION OF THE BEST HVAC SYSTEM FOR INDUSTRIAL BUILDINGS BY USING MULTI-CRITERIA DECISION-MAKING TOOLS(2022-01-20) ALALOOSI, KHALID; BAÇ, Uğur; TURHAN, CihanHeating Ventilating and Air Conditioning (HVAC) selection is a difficult task, especially when the selection relates to technical, economic, and environmental criteria. HVAC systems are responsible for 50% of total energy consumption in buildings and play a major role in the ability to reduce harmful emissions. The great demand for energy and the upward trend in the use of HVAC systems with the global need to impose measures on environmental hygiene underlines and focuses the importance of choosing the most appropriate HVAC system during the design process. The case study of an industrial building in Ankara has several machines studied. The Design Builder (DB) program was used in the dynamic building energy simulation and knowledge of the total energy consumption of the building. Stepwise Weight Assessment Ratio Analysis (SWARA) and Weighted Aggregated Sum Product Assessment (WASPAS) methods has been applied for the purpose of decision making due to its ability to accurately weigh criteria and to choose the most appropriate alternative through subjective and objective assessments with great accuracy. WASPAS is characterized by its ability to facilitate the effective data and vague information and to provide a good systematic decision-making analysis. Eleven HVAC systems were examined based on 27 criteria, including technical, environmental, and economic criteria. The results of selecting the best HVAC system using SWARA and WASPAS showed Sensitivity analysis performed according to different lambda values. The (Water-source Heat Pumps) is preferred at the first rank in all cases and it was identified as the best alternative for industrial buildings. It has been determined that the choice of alternative is economically, technically and environmentally most logical.Item STRATEGIC ENERGY PRODUCTION PLANNING OF TURKEY USING MIXED INTEGER PROGRAMMING BASED ON ELECTRICITY DEMAND FORECASTING(2022-01-11) YÖRÜK, GÖKAY; BAÇ, Uğur; YERLİKAYA ÖZKURT, FatmaIn this thesis, energy planning problem for Turkey is considered in terms of strategic planning, energy policy, energy power capacity planning, technology selection, and environmental policies. In strategic electricity planning, a mixed integer mathematical programming model is proposed that considers alternative technologies such as fossil fuels, renewable energy, nuclear energy, etc. In research problem, a set of energy resources are considered simultaneously and in addition to cost minimization (investment costs, operation, and maintenance costs), different strategic level policies such as minimization of CO2 emissions, energy resource share restriction policies, and renewable energy promotion policies are also taken into account. To forecast electricity demand during the planning horizon a set of forecasting techniques such as regression methods, exponential smoothing, Winter’s method, Autoregressive Integrated Moving Average (ARIMA) methods are used, and best method is selected using different error measures. As an application of the model, Turkey Strategic Electricity Planning Problem is studied, and it is solved for two different (2021-2030 and 2021-2040) planning intervals. The results show that use of renewable energy generation options namely solar, wind and hydroelectric alternatives will increase significantly while use of fossil fuels in energy generation will decrease sharply. In conclusion, this research recommends increasing renewable energy investments gradually and replace fossil fuel alternatives in the long run. This change will not only lower investment, operation, and maintenance costs both also produces lower emissions.Item STRATEGIC PLAN MEASUREMENT AND EVALUATION TOOL (SMET) FOR ORGANIZATIONS(2022-02-28) Kuyrukçu, Ayşe; Özkil, Altan; Özaktaş, HakanThe corporate level performance evaluation for strategic management has become a challenge for business world. Over time, many performance measurement techniques have been developed and used to measure strategic level performance. There are some models and methodologies developed for this purpose. An outstanding approach, Balanced Scorecard (BSC), developed by Kaplan and Norton in 1992, has become popular and has been successful in comparison to others. The primary weakness of all these methods is not to offer clear answers about how the performance criteria defined at the operational level should be reflected to the top of strategic plan’s hierarchy. What is common in most implementations is to adjust the company constraints to make them suitable with the solution tool with the help of expert and technical support instead of tayloring the solution tool to company needs. This would mean the renewal of the strategic plan of the company disregarding the older one and hence an unpreferable option in most cases. In this study, a methodology was developed by using Saaty scale for prioritization and Simple Additive Weighting Method (SAW) in reflecting the upper level categorization of operational level. With the addition of Simple Multi Attribute Rating Technique (SMART) method to this methodology, a novel decision support system software, called SMET (Strategic-plan Measurement and Evaluation Tool) has been developed. An organization which prepares a strategic plan may measure and evaluate its success ratio to satisfy all its objectives and aims with different set of priorities by providing actual and ideal performance indicators using SMET. An organization which identifies its current strategic plan in SMET will be able to calculate the realization ratio of the firm's strategic plan within seconds based on the five different prioritization methods in the system (scoring, ranking, pairwise comparison, weighted pair-wise comparison and user's own choice).Item STRATEGY DETERMINATION OF SMALL AND MEDIUM ENTERPRISES A COMPARISON OF TURKISH AND LIBYAN ENTERPRISES(2022-02-25) Elmabrouk, Walid; Erkan, ErmanThe success and performance of SMEs is known to drive the growth of the economies worldwide, as the majority of the jobs and business volume is attributed small and medium enterprises. Therefore, the continuous establishment, survival and growth of SMEs is considered a key strategy for any economy to stay healthy. In this research, several aspects of SMEs success factors and key performance indicators (KPIs) are studied through the literature review and the case study. A read through the literature contributed into compiling a list of key performance indicators for the success and performance and SMEs. Moreover, an Analytical Hierarchy Process (AHP) method is used in a case study in order to evaluate a strategy for the SMEs success and growth in Turkey and Libya. The KPI’s are used as criteria and sub-criteria for the feedback of the experts from both countries on the most important items to be considered in the SME strategy through a pairwise comparison between them. In Turkey, the results of the study showed innovation as the most important main criteria in SMEs success and growth, while management and human resources, and financial performance are indicated as the most important main criteria for Libya. Furthermore, flexibility in facings risks, R & D focus, and laws and regulation in support of the SMEs, are concluded as the most important sub-criteria for Turkey. Understanding customer and market conditions, knowledge competency, and management strategies are concluded among the most important sub-criteria for SMEs’ success and growth in Libya. Based on the results of the research, recommendations are provided for both case studies in order to empower SME’s development.Item SUPPLIER SELECTION BY TOPSIS METHODS PILOT STUDY FROM IRAN(2017-01-07) Gholamrezanezhad, Farshid; Erdebilli, BabekThis thesis provides a statement of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for the Multi-Criteria Decision-Making (MCDM) problem, and reviews the Supplier Selection (SS). The SS is figured out by MCDM methods and all the comparisons and discussions about SS held in brief. The study employs an evaluation methodology based on TOPSIS. The supplier selection problem is formulated utilizing the TOPSIS and then utilized to determine the weights of the criteria by considering the effects of interference and the relationship among the selection criteria. The present model provides an accurate and easy classification of supplier variables using a TOPSIS model. A numerical example is given to clarify the results improved in this case.Item THE HUMAN RESOURCES MANAGEMENT PERFORMANCE EVALUATION IN DIFFERENT SECTOR: (OIL SECTOR AND LOGISTIC SECTOR)(2022-02-25) Ramdan, Hanan Ramdan Saad; Erkan, Turan ErmanThe aim of this study was to assess the human resources management performance evaluation in different sector to shedding light on the different aspects of the human resources management reality and to determine the extent of employee have awareness of the impact of human resources management on the efficiency of institutions in different sectors. In this research, the impact of Human Resource Management (HRM) performance on institution has been studies in two sector, as Oil Industry institutions sector (Mellitah refinery of Oil & Gas), and as logistic and transport sector (Benghazi port). The study used the questionnaire tool to answer the study questions and test hypotheses and the Caronbach's Alpha test was used to measure he stability coefficients. The research current data that analyzed by Independent T-Test using SPSS software was supported the hypothesis. Moreover, the results of the study showed the human resources management policies and plans at different levels. Where, the employees showing that the HRM performance has high direct effect on company, and the impact is different between Oil Industry institutions sector (Mellitah refinery of Oil & Gas) and as logistic and transport sector (Benghazi marine portItem THE INFLUENCE OF SUPPLY CHAIN MANAGEMENT PRACTICES ON OPERATIONAL PERFORMANCE AND CUSTOMER DEVELOPMENT IN STARTUPS(2022-06-12) OLUDO, Steffany Atieno; ERKAN, Turan Erman; DURAL SELÇUK, GözdemStartups are becoming increasingly important contributors to many economies around the world. However, research indicates that certain shortcomings hinder the chances of startup survival. The ability to successfully attract, satisfy, and retain required number of customers to keep a startup in operation is critical for its survival. Supply chain management (SCM) has been identified among the most important management functions for gaining long-term competitive advantage. This study proposes that implementing SCM practices effectively can help startups improve their operational performance and consequently their customer development capabilities. This study empirically investigates the multidimensional relationships between SCM practices, operational performance, and customer development in startup organizations. The study employs a newly developed research framework based on existing theoretical evidence which explores four dimensions of SCM practices: (1) Strategic supplier partnership; (2) Information integration; (3) Information quality; and (4) Customer relationship. The effects of these four SCM practices are tested on three operational performance measures, namely quality, delivery, and cost. The study aims to demonstrate the respective contributions of different SCM practices to different operational performance measures, as well as the respective contributions of these measures to customer development in a hierarchical way. Data for the study is collected using survey questionnaires among supply chain professionals in startup companies in Kenya and ten hypotheses are tested simultaneously using structural equation modeling (SEM). The research is the first to look at the relationships among SCM practices, operational performance, and customer development in startups in one holistic framework. The study hopes to provide those startup practitioners who seek to maximize the operational performance and customer development capabilities with strategic insights to assist them in the effective adoption of SCM practices.